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									             Research methods
               “an overview”
                Dr. Tarek Tawfik

11/14/2010              Dr. Tarek Tawfik   1
 More than a set of skills, it is away of thinking:
  examining critically the various aspects of day to day
  professional work;
 Understanding and formulating guiding principles that
  govern a particular procedures;
 Developing and testing new theories for the
  enhancement of your practice.
  It is the habit questioning with systematic examination
  of the observed information to find answers which may
  results in more effective professional services. Kumar R 2005.
11/14/2010                  Dr. Tarek Tawfik                   2
    Research is a structured inquiry that utilizes acceptable
    scientific methodology to solve problems and creates new
    knowledge that is generally applicable. Grinnell 1993

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                        Types of research

                           Objectives                 Inquiry mode

      research                                        Quantitative
                 Descriptive            Exploratory
                  research               research

                 Correlational          Explanatory         research
                   research              research
       Research process “the 8 steps model”
                  Research design:      Methods and          Sampling theory       Methods of data
FINER             functions                                                         Processing:
                                        tools of data        and designs                                  Principles of
                                        collection                                   computers          Scientific writing
        Literature                                                                  and statistics

  Formulating                    Instruments                       Research     Data
                 Research         for data
                                                 Selecting         protocol
                                                                                              Data            Research
  a research                                     a sample                       collection    processing      report
                 design           collection                       writing

                                                                         Editing                     Coding
                 Study designs                                                         Code
                                                     Field test                        book
                                                    of the tools
                              Validity and
                            reliability of the                        Contents of
   Variables and              research tool                        research proposal
hypotheses: definition
    and typology

   What                                    How                                         Conducting of the study
   The structure of a research project is set out in
   its protocol, the written plan of the study.

The functions of the protocol are:
 Seeking grant funds.
 Helping the investigator to organize his research in a
  logical, focused, and efficient way.

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 Elements of protocol                         Purpose
Research questions          What questions will the study address?
Significance (background)   Why are these questions important?
Design                      How is the study structured?
  time frame
  epidemiologic approach
Subjects                    Who are the subjects and how will they be
    selection criteria      selected?
    sampling design
Variables                   What measurements will be made?
    predictor variables
    outcome variables
Statistical issues          How large is the study and how will it be
    hypotheses              analyzed?
    sample size
    analytic approach
              I- Conceiving the Research Question.

 The research question is the uncertainty about
 something in the population that the
 investigator wants to resolve by making
 measurements on his study subjects.

No shortage of questions as one leads to

 11/14/2010                    Dr. Tarek Tawfik      8
 Tamoxifen and Cancer Breast.

   Tamoxifen reduces the risk of cancer breast
   during 4 years of use by women at high risk of
   breast cancer.
Many other questions evolved:
o Does tamoxifen reduce the risk of death due to breast
o How long should treatment be continued?
o Might other drugs with the same action are beneficial
  without the risk of tamoxifen-induced thromboembolism?
o Does the use of such drug increases the risk for other cancer
                        The difficulty in question lies in
                        finding one that can be transformed
                        into a feasible and valid study plan.

 11/14/2010                  Dr. Tarek Tawfik                     9
Origins of a research question.
 For established investigator:
 The best research questions usually emerge from
  findings and problems faced and observed in prior
  studies, and in those of other workers in the field
  “Major Players”.
 For new and other investigators:
☼     Mastering of the literature.
☼     Being alert to new ideas and techniques.
☼     Keeping the imagination roaming.
☼     Attending seminar, workshops and conferences.

11/14/2010                Dr. Tarek Tawfik              10
Characteristics of a good research question “FINER Criteria”.

  Feasible                 Adequate number of subjects.
                           Adequate technical expertise
                           Affordable in time and money
                               Manageable in scope
Interesting                     To the investigator

   Novel                Confirms or refuses previous findings
                             Extends previous findings
                               Provides new findings
 Relevant                     To scientific knowledge
                            To clinical and health policy
                            To future research directions
Developing the research question and study plan.

☼ A one or two page outlining the study question
  and the study plan at an early stage is very
☼ This will focus the attention to clarify the ideas
  about the plan and to discover potential specific
  problems that need correction.

11/14/2010             Dr. Tarek Tawfik            12
 The research question should specifies!

Predictor      Exposure         Smoking

Confounders   Confounders   Occupational hazards

Outcome        Disease       Cancer lung
            The research question and study plan: problems and solutions
         Potential problem                                   Solutions
 The research question is not FINER
1- Not feasible
  too broad                              Specify a smaller set of variables
                                         Narrow the question.
  not enough subjects available          Expand the inclusion criteria
                                         Eliminate or modify exclusion criteria
                                         Add other sources of subjects
                                         Lengthen the time frame for entry into study
                                         Use strategies to decrease sample size
  methods beyond the skills of the       Collaborate with those who have skills
     investigator                        Consult and review the literature for alternative
  too expensive                          Consult and modify the research question

2- Not interesting, novel, or relevant
3- Uncertain ethical suitability

The study plan is vague
Consider the following research questions.
First, write each question in a single sentence
 that specifies a predictor, outcome, and
Then discuss whether it meets the FINER
  Rewrite the question in a form that overcomes
 any problems in meeting their criteria.

11/14/2010           Dr. Tarek Tawfik              15
A.     What is the relationship between depression and
B.     Does eating red meat cause cancer?
C.     Does lowering serum cholesterol prevent heart
D.     Can a relaxation exercise decrease the anxiety
       associated with mammography?
E.     Do contraceptive vaginal sponges prevent HIV
F.     Does dietary pattern among school children affect
       their health?
11/14/2010                 Dr. Tarek Tawfik                16
        Formulate a research questions regarding health
        and health-related problems that may be
        encountered in:

A.       Rural community and the available health facilities.
B.       Urban primary health care facility.
C.       Primary schools.

     11/14/2010                  Dr. Tarek Tawfik               17
II- Rationale (Significance).
     This section sets the proposed study in context and gives
     its rationale:
    What is known about the topic at hand?
    Why is the research question important?
    What kind of answers will the study provide?

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Rationale “Background”
۞This section cites previous research that is relevant
 (including the investigator‟s own work) and indicates
 the problem with that research and what question

۞It makes clear how the findings of the proposed study
  will help
o In resolving uncertainties,
o Leading to new scientific understanding and
o Influencing clinical and public health policy.

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              Sequence of the rationale
              In a concise logical sequence:
 Discuss the importance of the topic
 Review the relevant literature and current
  knowledge (including deficiencies in
  knowledge that make the study worth doing).
 Describe any results you have already obtained
  in the area of the proposed study.

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             Sequence of the rationale
Indicate how research question has emerged
 and fits logically with the above.

Outline in broad terms how you intend to
 address the research question.

Explain how your study will add to
 knowledge and help to improve health
 and/or save money.

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  How to determine research priorities?
I- How frequent is the condition relative to other
                    As a cause of death
II- What is the degree of disability or dysfunction due to
   the condition?
III- Are there cost-effective means to cure, control, or
   prevent such condition?

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    State the rationale (significance) for the
    proposed study question?

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     III-Setting up research objectives.
             Purpose broad objectives (aims)
☼    The statement of a research project should describe the
     main questions to be addressed by the research without
     going into details.
☼    It should give a reader a clear idea of the nature of the
     research that will be undertaken.

„ The purpose is to measure the effect of a plasmodium falciparum asexual
    blood-stage vaccine in reducing morbidity and mortality due to malaria‟
„ This study is conducted to assess the nutritional problems among primary
    school children‟

11/14/2010                         Dr. Tarek Tawfik                           24
               Specific objectives

The specific objective should be   SMART:
S            Specific
M            Measurable (effect size)
A            Applicable, achievable
R            Relevant
T            Timely (a time frame and end point).

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        Objectives “characteristics”

Clear         Complete             Specific           Identify the          Identify the
                              +                 +   Main variables     +   direction of the
        +                                           to be correlated         relationship

            Descriptive studies

    Correlation studies (experimental and non experimental)

                                  Hypothesis-testing studies
          Specific objectives in research
  They should include a concise but detailed
  description of:
o The intervention (study) to be evaluated,
o The outcome (s) of interest,
o And the population in which the study will be

 11/14/2010             Dr. Tarek Tawfik          27
Why is asthma among children in Istanbul
exceptionally frequent?

The purpose of the study are to determine if the
excess asthma in Istanbul is related to a
combination of genetic predisposition
(estimated by atopy) and socio-economic and/or
indoor air pollution.

11/14/2010              Dr. Tarek Tawfik      28
 What are the specific objectives to achieve such
 type of study?
I.     Identify a suitable source of childhood asthma cases and select
       200 cases, following a specific case definition.

II.    Identify and select suitable control subjects (individuals without

III.   Measure indoor particulate exposure on each of 3 randomly
       selected days for each participant.

IV.    Perform allergy skin test on cases and controls (atopy).

V.     Record personal, demographic, and socio-economic information
       about cases and control.

VI.    Compare risk ratio for atopy, low socio-economic status, and
       increased indoor air pollution between cases and controls.
       Hypotheses and
     Underlying Principles
                Dr. Tarek Tawfik

11/14/2010       Dr. Tarek Tawfik   30
Hypothesis definition
         A hypothesis is written in such a way that it can be proven or
         disproved by valid and reliable data-it is in order to obtain these data
         that we perform our study. Grinnel 1988:200.

Hypothesis has certain characteristics:
1.  It is a tentative proposition “hunch”
2.  Its validity is unknown.
3.  In most cases, it specifies a relationship between two or more

11/14/2010                            Dr. Tarek Tawfik                              31
               Functions of hypothesis
 Formulation of a hypothesis provides a study with focus
  “specific aspects of a research problem to investigate”
 What data are necessary to collect to test the hypothesis.
 Enables you to specifically conclude what is true or what is

                         Process of testing a hypothesis

             Phase I                  Phase II                     Phase III

        Formulate your                 Collect the         Analyze data
                                       required            To draw conclusions
        Hunch or
                                       data                About the hunch-true/false

11/14/2010                        Dr. Tarek Tawfik                                32
  It is the further formulation of the study
  question into a final and more specific
  version, that summarizes
    the elements of the study;
    the sample, the design,
    and the predictor and outcome variables.

The primary purpose is to establish the basis for
         tests of statistical significance.
 11/14/2010          Dr. Tarek Tawfik           33
I- Hypotheses are not needed in descriptive studies
   which describe how characteristics are distributed
   in a population.
    The prevalence of particular genotype among
    patients with hip fracture.

II- Hypotheses are needed in most of the observational
    and experimental studies that address statistical
    The study of weather a particular genotype is more
    common in patients with hip fracture compared to
 11/14/2010              Dr. Tarek Tawfik                34
       If any of the following terms appear in the
       research question, then the study is not descriptive
       and a hypothesis should be formulated:

      Greater than, less than, causes lead to, compared with, more
      likely than, associated with, related to, similar to, or
      correlated with.

11/14/2010                     Dr. Tarek Tawfik                      35
     Characteristics of a good hypothesis
              Simple, Specific, Stated in advance (3Ss)

           A-Simple versus complex
Contains one predictor and one outcome variable;
(a sedentary lifestyle is associated with an increased risk of
   proteinuria in patients with diabetes).

A complex hypotheses contains more than one
(a sedentary lifestyle and alcohol consumption are associated
    with increased risk of proteinuria in patients with diabetes).

 11/14/2010                      Dr. Tarek Tawfik                    36
                 Simple hypotheses
Or more than one outcome variable;
(alcohol consumption is associated with an increased risk of
    proteinuria and neuropathy in patients with diabetes).

    Complex hypotheses can be readily tested with a
    single statistical tests and can be easily approached by
    breaking them into two or more simple hypotheses.

  11/14/2010                   Dr. Tarek Tawfik                37
              Simple hypotheses
      (smoking cigarettes, cigars, or a pipe is
       associated with an increased risk of proteinuria
       in patients with diabetes).

What type of hypotheses is this?

11/14/2010                Dr. Tarek Tawfik            38
                 B-Specific versus Vague

      A specific hypothesis leaves no ambiguity about the subjects,
       the variables, or about how the test of statistical significance
       will be applied.
      it uses concise operational definitions that summarize the
       nature and source of the subjects and how variables will be
       (a history of using tricyclic antidepressant medications, as
       measured by review of pharmacy records, is more common in
       patients hospitalized with an admission diagnosis of
       myocardial infarction at Longview Hospital in the past year
       than in control hospitalized for pneumonia).

    11/14/2010                   Dr. Tarek Tawfik                   39
               Specific versus Vague
      It is often obvious from the research hypothesis
       whether the predictor variable and the outcome
       variable are dichotomous, continuous, or
       (alcohol consumption (in mg/day) is associated with an
       increased risk of proteinuria (> 30 mg/dL) in patients with

11/14/2010                      Dr. Tarek Tawfik                     40
     C-In Advance versus After-the-Fact
      The hypothesis should be stated in writing at the
       outset of the study.
      A single pre-tested hypothesis creates a stronger basis
       for interpreting the study results than several
       hypotheses that emerge as a result of data inspection.
      Hypotheses that are formulated after data examination
       are a form of multiple hypothesis testing that often
       leads to over-interpreting the importance of the

11/14/2010                   Dr. Tarek Tawfik                41
                  Types of hypothesis

Alternate hypothesis                             Research hypothesis

                                      Hypothesis       Hypothesis       Hypothesis
                                     of difference      of point-      of association
Null hypothesis                                        prevalence

                        of no difference
                       “null hypothesis”
Types of hypothesis “examples”
     There is no significant difference in the proportion of
     male and female smokers in the study population.
     Hypothesis is ?
     A greater proportion of females than males are smokers
     in the study population. Hypothesis is ?
     A total of 60% of females and 30% of males in the study
     population are smokers. Hypothesis is ?
     There are twice as many female smokers as male
     smokers in the study population. Hypothesis is ?

11/14/2010                 Dr. Tarek Tawfik                43
                Types of Hypotheses
               1- Null and Alternative
I- The null hypothesis states that there is no association
   between the predictor and outcome variables in the
    (there is no difference in the frequency of drinking well water
    between subjects who develop peptic ulcer disease and those who
    do not).
II- It is the formal basis for testing statistical significance.
     Statistical tests help to estimate the probability that an
     association observed in a study is not due to chance.

 11/14/2010                      Dr. Tarek Tawfik                 44
              Null and Alternative
o The proposition that there is an association is
    called the alternate hypothesis.

o The alternative hypothesis cannot be tested
    directly; it is accepted by default if the test of
    statistical significance rejects the null
    hypothesis. “accepted when null is rejected”

 11/14/2010              Dr. Tarek Tawfik                45
2- One and Two-sided alternative Hypothesis

I- A one-sided hypothesis specifies the direction of
  the association between the predictor and the
  outcome variables.
      Drinking well water is more common among subjects who
      develop peptic ulcer (one-sided).

II- A two-sided hypothesis states only that an
    association exists; does not specify the direction.
      The prediction that subjects who develop peptic ulcer
      disease have a different frequency of drinking well water
      than those who do not (two-sided).
11/14/2010                    Dr. Tarek Tawfik                    46
For one-sided:
 When only one direction for an association is
  important or biologically meaningful (a new drug
       for hypertension is more likely to cause rashes
       than a placebo).

      When there is good evidence from prior studies
       that an association is unlikely to occur in one of
       the two directions (smoking affects the risk of
       cancer brain).
11/14/2010                  Dr. Tarek Tawfik                47
     Underlying Statistical Principles

                           Study plan                  Actual study
Research Q

                           Intended                     Subjects
Population     Random                      Random
Phenomena     Systematic                  Systematic    Actual
Of interest     error                       error       Measure.

Truth in                    Truth in        infer
               infer                                   in the study
Universe                   the study
           Underlying Statistical Principles
            Jury decision                                      Statistical tests

Innocence: the defendant did not       Null hypothesis: there is no association between dietary
counterfeit money                      carotene and incidence of colon cancer.
Guilt: the defendant counterfeit       Alternative hypothesis: there is an association between
money                                  dietary carotene and colon cancer incidence.
                                       Standard for rejection null hypothesis:
Standard for rejecting innocence:      Level of statistical significance ( ≤ 0.05)
beyond a reasonable doubt.
Correct judgment: convict a            Correct inference: conclude an association when one does
counterfeiter                          not exist in the population.
Correct judgment: acquit an innocent   Correct inference: no association between carotene and
person                                 colon cancer when one does not exist

Incorrect judgment: convict an         Incorrect inference (Type I error): association in the study
innocent person                        when actually is none
Incorrect judgment: Acquit a           Incorrect inference (Type II error): there no association
counterfeiter                          when actually there is one.
             Type I and type II error
    A type I error (false-positive) occurs if the
    investigator rejects a null hypothesis that is actually
    true in the population.

    A type II error (false-negative) occurs if the
    investigator fails to reject a null hypothesis that is
    actually not true in the population.

11/14/2010                  Dr. Tarek Tawfik                 50
 Truth in the population Vs. the results in the study
 sample (the four possibilities).

                               Truth in the population
 Results in the study sample      Association between    No association between
                                 predictor and outcome   predictor and outcome
Reject null hypothesis                    Correct          Type I error

Fail to reject null                Type II error              Correct

 11/14/2010                     Dr. Tarek Tawfik                           51
             , and Power
 The probability of committing a type I
  error (rejecting the null when it is
  actually true) is called  (alpha), another
  name is the level of statistical
 An  level of 0.05, setting 5 % as the
 maximum chance of incorrectly
 rejecting the null hypothesis.

11/14/2010          Dr. Tarek Tawfik            52
 The probability of making a type II error (failing to reject the
  null hypothesis when it is actually false) is called  (beta).

 The quantity (1-  ) is called power, the probability of
  rejecting the null hypothesis in the sample if the actual effect
  in the population equals effect size.

 If  is set at 0.10, we are willing to accept a 10 % chance of
  missing an association of a given effect size. This represents a
  power of 90 % (there is 90 % chance of finding an association
  of that size).

 11/14/2010                   Dr. Tarek Tawfik                  53
                          P Value
       A „non significant‟ result (i.e., one with a P value
        greater than ) does not mean that there is no
        association in the population, it only means that
        the result observed in the sample is small
        compared with that occurred by chance

       Those with hypertension were twice as likely to
        develop cancer prostate compared to normotensive
        subjects (P of 0.08)

    11/14/2010                Dr. Tarek Tawfik                 54

                      Dr. Tarek Tawfik

11/14/2010     Dr. Tarek Tawfik          55
 In research what we are looking for?

The variable: is a condition, quality or trait that
varies from one case to another Provokes research
In the target population (population of interest)
                          To study these
  Either include the
      Population                           Sample
             Basic Terms and Concepts
               Target Population and Sample
o A population is a complete set units with a specified set of
  characteristics while a sample is a subset of that population.
o The defining characteristics of population include geographic,
  clinical, demographic and temporal.
o Clinical and demographic characteristics define the target
  population, the large set of people throughout the world to
  which the results will be generalized.
                     (all teenagers with asthma).
o The study sample is the subset of the target population available
  for study.
      (teenagers with asthma in the investigator‟s town in 2005).
 Steps in designing the protocol for choosing the
                  study subjects

  Research question                      Study plan

         Target                          Intended sample
       population                       Specify accessible
      Specify clinical,
                                         population and
   Demographic and then
  Geographic and temporal             approach to selecting
      characteristics                       the sample

Truth in the Universe                Findings in the study
                    Selection Criteria

 How        would you define the population to be studied?

 Through     establishing selection criteria that include
     inclusion and exclusion criteria.

    Demonstrate the selection criteria for subjects to
    evaluate the efficacy of calcium supplements for
    preventing osteoporosis?

11/14/2010                    Dr. Tarek Tawfik                59
         Designing selection criteria for a clinical trial of calcium
                  supplements to prevent osteoporosis

                    Considerations                     Example
Inclusion       Specifying the characteristics    A 5-year trial of calcium
criteria        that define population that are   supplementation for preventing
(be specific)   relevant to the research          osteoporosis might specify the
                question and efficient for        subject be:
                ®Demographic: age, sex, and       White females 50 to 60 years old
                ®Clinical characteristics.
                                                  In good general health**
                ®Geographic (administrative).
                                                  Patients attending clinic at X
                ®Temporal   characteristics       Between Jan. 1st and December
                                                  31st of next year.
           Designing selection criteria for a clinical trial of calcium
                    supplements to prevent osteoporosis

                         Considerations                  Example
Exclusion           Specifying the subsets of the   The calcium supplementation trial
Criteria            population that will not be     might exclude subjects who are:
                    studied because of:
(be parsimonious)

                    A high likelihood of being     oAlcoholic or plan to move of the
                    lost to follow-up.              country or region.
                    An inability to provide good   oDisoriented or have a language
                    data.                           barrier.
                    Being at high risk of side     oSarcoidosis /hypercalcemia.
                    Characteristics that make it
                                                    oTaking   steroids.
                    unethical to withhold the
                    study treatment
        Clinical versus Community populations

If the research question involves              In choosing the sample in the
    patients with a disease;                      community who will
    hospitalized or clinic-based                  represent a non clinical
    patients are inexpensive and easy             population (population-
    to recruit, but selection factors             based)
    that determine who comes to the            Samples are difficult and
    hospital or clinic may have an                expensive to recruit, but they
    important effect.                             are particularly useful for
                                                  guiding public health and
Tertiary clinics tend to                          clinical practice in the
  accumulate patients with                        community.
  serious forms of disease.

  11/14/2010                     Dr. Tarek Tawfik                            62
                Studying The whole population
    Resorted to if we are interested in the characteristics of each
     individual, particularly with descriptive research questions, and
     there is a need for generalizing the findings.
    Probability sampling is the gold standard.
    It provides a rigorous basis for estimating the fidelity with
     which phenomena observed in the sample represent those in
     the population, and for computing statistical significance and
     confidence intervals.

    A.   It is expensive.
    B.   It is time consuming.
    C.   It has higher error chances because of the many persons,
         equipments and wide geographic area covered.
    D.   Carried out in censuses.
      Resorted to if we are interested in studying the prevalence of a
      problem, associations or intervention effect,…..etc

 A.          It is less expensive.
 B.          It is less time consuming.
 C.          It has lower error chances because of less persons,
             equipments and geographic area covered.
 D.          Only estimates are concluded, the reality is unknown.
 E.          It allows for continuous study of the population
             “longitudinal studies”.

 Study of a sample is carried out in the majority of
     biomedical researches.
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              The concept of sampling

      Study population:   You select a few sampling units
         Sampling units                                            Sample
                            from the study population

                  You make an estimate “prediction”
                 extrapolated to the study population       You collect information
                     (prevalence, outcomes etc.)             from these people to
                                                             find answers to your
                                                              research questions.

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          Principles of sampling
I.   In a majority of cases of sampling there will be a
     difference between the sample statistics and the true
     population mean, which attributable to the selection of
     the units in the sample “sampling error”.
II. The greater the sample size, the more accurate will be
     the estimate of the true population mean “reduction in
     sampling error”
III. The greater the difference in the variable
     “heterogeneous variable” under study in a population
     for a given sample size, the greater will be the
     difference between the sample statistics and the true
     population mean “the larger the sampling error”.
                     Types of sampling

                                       Non-random/probability      Mixed sampling

 Simple       Stratified            Cluster      Quota                  sampling


 Proportionate             Single             Accidental

Disproportionate                              Multi-stage         Snowball
                      Double stage
                Types of Samples

   Probability samples:
         Units are selected according to probability laws i.e.
        everyone in the underlying population has an equal (a
        specified) and independent chance of appearing in
        that sample.

   Non-probability (convenience) samples:
    Units are selected based on known factors.
    In clinical research the study sample is usually made up of
      people who meet the inclusion criteria and are easily
      accessible to the investigator.
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             Probability Samples
  In order to be able to infer from sample results to the
  underlying population, that sample should be a
  representative sample.
      i.e. it should represent the population from which it is
       drawn in every respect.

    Because we can not anticipate all characteristics of
      the population that the sample should represent,
          we chose a probability (random) sample.

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             How to draw a probability Sample?
I.   Identify the study units (individuals, villages,
     houses, …etc).
II. Make a complete list of the study units in the
     underlying population. That complete list is
     known as the sampling frame.
III. Each of these units is given a number.
IV. Then select the required number of units (sample
     size) at random from that frame.

     11/14/2010             Dr. Tarek Tawfik        70
The selection of units can be made either by:

1.   The lottery method “fishbowl draw” (the
     numbers of frame units are written on
     identical pieces of papers, mixed
     thoroughly in a bowl and the required
     number is blindly picked up).
2.   Through the use of random numbers tables.
3.   Computer generated random numbers.
Two systems of drawing a random sample:
  Sampling without replacement.
  Sampling with replacement.
Random number table
      Random Sampling Techniques

1-Simple random sample
2-Stratified random sample
3-Systematic random sample
4-Cluster random sample
5-Multistage random sample

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      1-Simple random sample
    We prepare a complete and up-to-date list of the underlying
    population (sample frame). The specified sample size is drawn
    from that frame at random.
            Suitable for homogenous population (single sex).
            Larger sample size is required.
            More expensive as we have to get the cases from
             widely scattered areas.
            Time consuming and more laborious.
            Some groups might not be represented in the sample.
            Extreme values can occur by chance.

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Example of Simple random sample using random digit table.

      Draw at random a sample size of 50 from a
                 population of 10,000.

 A.     The size of the population is 10,000 i.e. it is formed of 5 digits.
 B.     Select at random a page from the random numbers table
 C.     Select 5 adjacent columns
 D.     Proceed from up down, any value falling between 00001 and
        10,000 is chosen and so on until you completed your 50 cases.
 E.     Duplicate numbers are left aside
 F.     Individuals with those 50 numbers compose our sample.
The First 15 columns of the first page of a Random
numbers table

     26804               00010             93445
     90720               12805             58563
     85027               32242             86468
     09362               16212             00128
     64590               75362             32348
     29273               34703             23763
     96215               01556             63708
     59207               22211             48522
     49674               01534             98685
     04104               00047             14986
2-Stratified random sampling
o Based upon the logic of heterogeneity of the
  included variables.
o Ensure homogeneity of sub-population though
  ranking them into strata.

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     2-Stratified random sample
   Ensures representativeness with regard to important
    characteristics as age, sex, educational or socio-
    economic levels.
   The population is divided into strata (subgroups)
    according to the different levels of the important
    variable. The population in each stratum is
    homogenous so sampling accuracy is increased.
   We choose a simple random sample from each
    stratum, the size of which is proportionate to the size
    of that stratum.
   In other words the sampling fraction is the same for
    each stratum and the total sample.
                n   n1   n2   n3
                          
                N   N1   N2   N3
 Example of Stratified random sample
A town with a total population of 12,000 was classified into 4
homogenous socioeconomic strata. The population in each
stratum was 2,000 (class I), 4,000 (class II), 5,000 (class III)
and 1,000 (class IV) respectively. A sample size of 600 is to be
drawn from the town. Calculate the number of individuals to be
drawn at random from each of the 4 strata?

Sampling        fraction        600
                                12, 000      1

Stratum1 sample  2000 x                      1
                                              20    100
Stratum2 sample  4000                    x   1
                                              20    200
Statum3 sample  5000                     x   1
                                              20    250
Stratum4 sample  1000                    x   1
                                              20    50
 3-Systematic random sample

1.    The underlying population is classified into intervals:
      The size of intervals = the size of the population ÷ the
      required sample size.

2.    The first case is selected at random from the first stratum
      (interval) and the others are selected by adding
      systematically the size of each interval.
3.    Accordingly we are taking each (nth) individual. n is the
      size of the interval. If the latter is 10 we take every tenth

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    Example of systematic random sample

        1000 patients visit King Faisal University outpatient
        clinics every day. We need a systematic random
        sample of 100 patients. Explain how should we
        proceed in selecting those 100 patients composing
        our sample?
   We classify the patients into 100 intervals and select a patient from
   Size of each interval =1000/100 = 10
   Choose at random a number that lies between 1 and 10 say 9.
   Choose from the second interval patient number 19 th.

   Choose from the third interval observation number 29 th.
       9  1x10  19 th              OR             9  10  19 th
       9  2 x 10  29 th           OR              19  10  29 th
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4-Cluster random sample

۞ In this method, the sampling units are clusters (groups) of
  individuals – (incomplete sampling frame and/or the total
  sampling population is large) rather than individuals.

۞ The clusters (schools, houses, villages, …etc.) form the sampling
  frame, from which the required number of clusters is selected at

۞ All individuals in a cluster, a specific group, or a random sample
  of them are included.

۞ Very useful when the population is widely dispersed, and it is
  impractical to list and sample from all its elements.

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Example of random cluster sample

   In some research, the objective was to study the
        prevalence of malnutrition among primary school
        children in Hofuof. There are 200 primary schools
        in Hofouf. The estimated sample size is 20
   Describe how would you proceed in drawing such
   A.    List all 200 schools
   B.   Give each a number
   C.   Use the random numbers tables in selecting the
        20 schools whose numbers will fall between 001
        and 200.

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5-Multistagerandom sample

         We use this method if the target population is spread
         over wide geographic area and there is limited budget or
         resources (in community-based surveys).

             In this method, the sample is drawn in many stages.

         The area is divided into smaller clusters, the clusters are
         divided into smaller clusters and so on. Random
         selection is carried out at each level successively.

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You were asked to head a research team to
   investigate the problem of handicapping in
   K.S.A. How would you proceed in drawing
   your sample?
             List all governorates
            Select 4 governorates at random
            List the districts in each of the 4 governorates
            Select a district from each governorate at random
            List all village and urban areas in each districts
            Select a village and an urban centre from each district
            Study all or sub-sample of individuals in the selected
             villages and urban centres

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             II-Non-probability (convenience) samples

    A convenience sample can minimize volunteerism and
     other selection biases by consecutively selecting every
     accessible person who meets the inclusion criteria.
    A consecutive sample is specially desirable when it
     mounts to taking the entire accessible population over
     a long enough period to include seasonal variation or
     other changes over time that considered important to
     research question.
    Representativness is a matter of judgment.

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             Non-probability samples

 These designs are used when the number of
  elements in a population is either unknown or
  can not be individually identified.
 Quota sampling.
 Accidental sampling.
 Judgmental or purposive sampling.
 Snowball sampling.

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Non-probability (convenience) samples

1-Purposive sample:
       Chosen according to the investigator‟s judgement in
       such a way that maximizes the chances of proving the
       study hypothesis. “selecting patients with ESRD”
2-Quota sample:
      Involves only few strata e.g. men and women >20
       years. The enumerators select any individual belonging
       to those strata from whom they get the required
       information in an easy, quick and accessible way.

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Sample size
How many observations should we include?
The greater the sample size:
  I.    The more precise are the estimates derived.
     II.     The more powerful are the tests (probability of
             rejecting a false null).
             Larger degrees of freedom and smaller test
                statistic required.
             Smaller standard error.
     III.    Higher costs, more time and efforts needed.

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Sample size
The size of the sample depends on:

1.    Study design,
2.    Maximum tolerable sampling error,
3.    Homogeneity of the population,
4.    Number of variables studied,
5.    The extent of breaking down the data in analysis,
6.    Cost,
7.    Available staff, equipments, time and tools,
8.    Statistical tests used.

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Data Collection Techniques and

                                   Dr. Tarek Tawfik

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             Objective of data collection
     Allow the investigator to systematically
     collect data about the subjects under the
     study including the setting in which
     they were occur.

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                      Methods of data collection

 Secondary                                                                 Primary
 Sources                                                                   Sources

Documents                  Observation                 Interviewing            Questionnaire

                    Participant           Structured                  Mailed
publications                 Non-participant           Unstructured              Collective
oEarlier research
oPersonal records
oClient histories
oService records
 Participant: the researcher participates in   the
  activities of the group being observed
  “submitted to clinical examination to observe
  practice of physicians”
 Non-participant: involved in the activities and
  remains a passive observer “functions carried
  out by nurses in a hospital”

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Problems with observation:
     Hawthorne effect: change in behavior as a result
     of the observation process.
     Observer bias.
     Inter-observer variation in interpretation.
     Incomplete observation and /or recording “keen
     observation with missing recording or vice

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             Recording of observation
    Narrative: description of the process in the researcher‟s
     own words “deeper insight in interpretation and
    Scales: interpreting in a form of rates using scales for
     measurements. No in-depth interpretation, error of
     central tendency and Halo effect.
    Categorical recording: yes/no, always/sometimes/never.
    Using mechanical devices: videotape “uncomfortable or
     behave differently before a camera or cassette recorder.

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Scale “example”
                         Positive             Neutral          Negative

                5    4      3       2     1         0      1   2   3      4   5

        Aggressive behavior of nurses in hospital Z

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                   Different levels of flexibility and specificity.
Unstructured                                                            Structured
Interviews                                                              Interviews

-Flexible interview structure.                          -Rigid interview structure.
-Flexible contents                                      -Rigid contents
-Flexibility in questions                               -Rigidity in questions and
In-depth interviews                                    their wording.
Focus group discussion                                 Interview schedule
Narratives                                             Questionnaire
Oral histories
             Techniques of data collection
 Using the available information (records and registries).
 Observing and recording using an observation check list.
 Interviewing (face to face)
 Self-administered questionnaire
 Telephone and net surveys.
 Focus group discussion.
 Measuring scales.
 Others (life histories, essay, case studies, and mapping).

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    Techniques of data collection
         (advantages and disadvantages)
Technique            Advantages                  Disadvantages

Records and   1.   Inexpensive              1.   Accessible.
 registries   2.   Permit examination of    2.   Non-ethical
                   past trends.             3.   Incomplete and
Observation   A.   More detailed            A.   Ethical issues
                   information.             B.   Observer bias
              B.   Facts not mentioned by   C.   Data collector may
                   questioning                   influence results.
              C.   Test reliability         D.   Need training.
        Techniques of data collection
               (advantages and disadvantages)
    Technique                  Advantages                          Disadvantages

Personal interviewing   I.     Suitable for illiterates   I.     Interviewer may influence
                        II.    Permits clarification             results
                        III.   High response rate         II.    Less accurate recording than
                                                          III.   Needs trained personnel
  Self administered     1.     Less expensive
    questionnaire       2.     Permit anonymity           1.     Not suitable for illiterate
                        3.     Less personnel             2.     Low response rate
                        4.     Eliminate bias             3.     Problem of misunderstanding
    Techniques of data collection
         (advantages and disadvantages)
  Technique              Advantages               Disadvantages

 Focus group      Collection of in-depth   1.   Interviewer may
  discussion      information and                influence results
                  exploration               2.   Open-ended questions
                                            3.   Domination
                                            4.   Non response

Measuring scale   oPrecision                o    Training
                  oEliminate   bias         o    Validity and accuracy
    Differentiation between data collection
             techniques and tools.
Techniques                              Tools

Using available data
                      Data compilation sheet
                      Check list, eye, watch, scales,
                       Microscope, pen and paper.
                      Schedule, agenda, questionnaire,

questionnaire          Questionnaire.
 Designing Questionnaire and Data
      Collection Instruments.
      In many instances the validity of the results
       depends on the quality of the data collection

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 Choosing between an interview schedule and a

 Nature of the investigation: reluctant to discuss
  “sexuality, drug use”.
 Geographical distribution of the study population.
 The type of study population. “illiterate, young,
  handicapped, very old”.

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Administration of questionnaire.
     Mailed or via other electronic media.
     Collective administration “people attending
     some function (schooling)”.
     Administration in a public place “hospital,
     medical center”.

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Advantages and disadvantages of questionnaire.

Advantages                       Disadvantages
1.     Less expensive            1.        Application is limited
2.     Offers greater            2.        Response rate is low
       anonymity                 3.        Self-selecting bias
                                 4.        Opportunity to clarify is
                                 5.        Spontaneous responses are
                                           not allowed.
                                 6.        Possible to consult others.

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     Advantages and disadvantages of interview.
             Advantages                       Disadvantages

1.   More appropriate for           1.   Time consuming and
     complex situations.                 expensive.
2.   Collecting in-depth            2.   Quality of data depends
     information.                        on the quality of
3.   Information can be                  interaction.
                                    3.   Quality of data depends
4.   Questions can be explained.         on the quality of
5.   Has a wider application “any        interviewer.
     type of population”
                                    4.   Many interviewers
                                    5.   Interviewer bias.
             Designing Good Questions and Instruments
             Open-ended and Closed-ended Questions

Open-ended question:
   Useful when it is important to hear what respondents
    have to say in their own words;
What habits do you believe increase a person’s chance
    of having a heart attack?
It leave the respondent to answer freely without limits that may
    imposed by the interviewer.

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        Designing Questionnaire and Data Collection Instruments.

Open-ended questions:
A.       Often used in exploratory phases of question design
         because they facilitate understanding a concept as
         respondent express it.
B.       Phrases and words used by respondent can form the
         basis for more structured items in a later phase.
   Usually require qualitative methods of coding and
   analyze the responses, which take more time and
   subjective judgment than coding closed-ended
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        Designing Questionnaire and Data Collection Instruments.

Closed-ended questions:
More commonly used, and form the basis for most standardized measures.
Ask the respondent to choose from one or more pre-selected answers;

    Which one of the following do you think increases a
    person’s chance of having a heart attack the most ?
    (Check one)


             Being overweight

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             Closed-ended questions:
        They quicker and easier to answer.
        The answers are easier to tabulate and analyze.
        The list of possible answers often help to clarify the
        meaning of the question.
i.  It may lead the respondent, and do not allow them
    to express their own, potentially unique answers.
ii. The potential responses listed may not include an
    answer most appropriate for a particular
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             Designing Questionnaire and Data Collection

  Whenever there is a chance that the set of answers is
  not exhaustive (does not include all the possible
  options), include the option „Other (please specify)‟ or
  „None of the above”
  When a single response is desired, the set of possible
  responses should be mutually exclusive „ the
  categories should not overlap‟ to ensure clarity.
  All that apply is used for multiple answer.

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                   The Visual Analog Scale

   Used for recording the answers to closed-ended questions using
    lines or other drawings.

   The participant is asked to mark a line at a spot, along the
    continuum from one extreme to another, that best represents
    his characteristics.

   It is important that the words that anchor each end describe the
    most extreme value for the item of interest.

   The line is 10 cm long and score is the distance, in cm from the
    lowest extreme.
         Visual Analog Scale for Rating the
                  Severity of Pain
  4- please use an X to mark the place on this line that best describe the severity of
  your pain in general over the past week

              None                                            Unbearable

   A participant might answer as follow

              None                                            Unbearable

There is a 10 cm line, and the mark is 3 cm from the end (30 % of the distance from
none to unbearable) so the respondent‟s pain would be recorded as having a severity of
30 %.
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        Formatting of questionnaire
   It is customary to describe the purpose of the study and how
    the data will be used in a brief statement on the cover together
    with name of the institution, assure anonymity, contact
    number for any questions, return address, deadline date and
    thank them for participation. “the covering letter”

   To ensure accurate and standardized responses, all instruments
    must have instructions specifying how they should be filled
   Some time it is helpful to provide an example of how to
    complete question, using a simple question that is easily
 To improve the flow of the instrument, questions concerning
  major subject areas be grouped together an introduced by
  headings or short descriptive statements. “personal data include:
  age, sex, educational status, marital status”
 To warm up the respondent to the process of answering
  questions, it is helpful to begin with emotionally neutral
  questions such as self-rated health of functioning.
 More sensitive questions can be placed in the middle.
 Questions about personal characteristics such as income or
  sexual function are often placed at the end of the instrument.

   The visual design should be as easy as possible for the
   respondent to complete all questions in the correct sequence.
   With too complex format, the respondent or interviewer may
   skip questions, provide wrong answers, and even refuse to
   complete the instruments.
   A plenty of space is more attractive and easier to use than one
   that is crowded.
   When open-ended questions are used, the space of responding
   should be big enough to allow respondent with large
   handwriting to answer comfortably.

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     People with visual problems, including elderly will
     appreciate large type (font size 14), and high contrast (black
     on white).
     Possible answers to closed-ended questions should be lined
     up vertically and preceded by boxes or brackets to check, or
     by number to circle, rather than open blanks:
    How many different medicines do you take every day?
    (Check one)
             7 or more

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                        The Branched Question:
    Sometimes the investigator may wish to follow up certain
    answers with more detailed questions:
    Respondent‟s answer to initial question (screener) determine
    whether they directed to answer additional question or skip
    ahead to later questions;
10- Have you ever been told that you have high blood pressure?
         Yes                               No
If yes, how old were you when you were first told that you had high blood pressure?
-------------- years old.
If no, go to question 11.

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             Clarity, Simplicity, Neutrality
        Every word in a question can influence the validity and
        reproducibility of the responses.
•       Constructed question should be simple and free of ambiguity.
•       Encourage accurate and honest responses without embarrassing or
        offending of the respondent.

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o    Question must be as clear as specific as possible.
o    Concrete words are preferred over abstract words:

How much exercise do you usually get?
             Is less clear than

“ during a typical week, how many hours do
  you spend exercising (e. g., vigorous walking
  or sports)?”
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   Simple and common wording should be used to
   convey the idea, avoid technical terms and jargon.

“ drugs you can buy without a doctor‟s prescription”.
Clearer than “over-the-counter medications”.

   The sentences should also be simple, using the fewest
   words and simplest grammatical structure.

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 Avoid Loaded words and stereotypes that
 suggest that there is a most desirable answer.

“During the last month, how often did you drink
  too much alcohol”

“During the last month, how often did you drink
  more than five drinks in one day”
              Less Judgmental question.
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  It is useful to set a tone that permits the respondent to
  express behaviors and attitudes that may be
  considered undesirable.

“ People sometimes forget to take medications their
 doctor prescribed. Do you ever forget to take your

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                    Avoid Pitfalls

I.           Double-Barreled Questions.
II.          Hidden assumptions.
III.         The question and answer options do not
IV.          Leading questions.

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   I- Double-Barreled Questions.

 Each question should contain only one concept
 :Or or And will lead to unsatisfactory responses.

 “How many cups of coffee or tea do you drink
 during a day?”.
  In this case you should ask two questions to assess two

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             II- Hidden Assumptions.
“How many cigarettes do you smoke in a day?”

“What contraceptives do you use?”

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      III-The question and answer options do not match.

“ Have you had pain in the last week”
 The options are : (never, seldom, often, very often),
grammatically incorrect:
“ How often have you had pain in the last week?” or the
  answer should change to (yes, no).

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The question and answer options do not match.

Question about intensity:
“ I am sometimes depressed” (agree) (disagree).

     For those who are often depressed, it is unclear to respond,
     disagreeing with this statement could mean that the person is
     often depressed or never depressed.
     (never, sometimes, and often) should be the options.

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             IV-Leading questions
    It is the one in which, contents, wording or
    structure leads a respondent to answer in a
    certain direction “judgmental questions”.

 “Unemployment is increasing, isn‟t it?”
 “Smoking is bad, isn‟t it?”

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Collecting data using attitudinal scales

                                   Dr Tarek Tawfik

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             Function of attitudinal scales
    Attitudinal scales measure the intensity of
    respondent‟s attitudes towards the various
    aspects of a given situation or issue and provide
    a techniques which combine the attitudes
    towards different aspects into one overall
    To develop an overall picture out of various
    opinions and perspectives.

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             Developing a scale
1. Which aspects is going to be measured?
2. Procedures adopted to combine these aspects
   to give an indicator for measurement?
3. The validity of such scale?

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               Types of attitudinal scales

Summated rating                              The cumulative
                       Differential scale
      Scale                                       Scale
                       “Thurstone sclae”
  “Likert scale”                             “Guttman scale”
             I-Likert Scale

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             Basic Research
                                    Dr. Tarek Tawfik

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        Definition of a research design
    A traditional research design is a blueprint or detailed
    plan for how a research study is to be completed-
o   Operationalizing variables so they can be measured,
o   Selecting a sample of interest to study,
o   Collecting data to be used as a basis for testing
    hypotheses and
o   Analyzing the results.
                                               „Thyer 1993‟

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                     Types of study design (I)

                                                                                              Classification base
                                                                               Nature of
Number of contacts                           Reference period                investigation

                                                                                             Study designs
                                                       Retrospective    Experimental

   One             Two            Three or more

                                                        Prospective     experimental

Cross-sectional                   Longitudinal
   Studies                          Studies
                                                        Retrospective        Semi-
                                                        Prospective       experimental
                   Before and
                  after studies
                                  Research designs (II)
              Did the investigator assign exposure “intervention”?
              Yes                                                     No

        Experimental study                                       Observational study

                                                            Comparison group?
       Random allocation?
                                                    Yes                                 No
Yes                                No

                                             Analytical study          Descriptive study
 Trial RCT                                          Direction?

                                                                      Exposure and outcome
                                                                         at the same time
                    Cohort                   Case-control
                     study                      study
              Exposure →outcome              Exposure ←outcome
                                 Phases and indications of basic study designs
  Type of         Timing              Form         Action in past       Action in       Action in future         Typical uses
   study                                               time            present time          time

  Cross-       Cross-sectional     Observational                                                           Prevalence estimates
 sectional                                                              Collect                            Reference range
                                                                          All                              Current health status
 Repeated      Cross-sectional     Observational
   cross-                                                  Collect     Collect     Collect                 Changes    over time
                                                             All         All         All
                                                         information information information
                Longitudinal       Observational                                      follow
                (prospective)                                       Define cohort                          Prognosis   and natural
                                                                     and assess                            history
                                                                     risk factors                          Etiology

Case-control                                                                                               Etiology particularly for
                Longitudinal       Observational     Assess         trace   Define cases
               (retrospective)                                              and controls                   rare diseases
                                                     factors                 (outcome)

    C.T                                                                               follow               Clinical trials to assess
                (prospective)      Experimental                         Apply                  Observe     Trials to assess
                                                                     intervention              outcome     preventive measures
                                                                                                           Lab. experiments
                      Descriptive Studies
                       The Descriptive Pentad

             Descriptive studies are „the first toe in the water‟
 They concerned with and designed only to
 describe the existing distribution of variables
 without regard to causal or other hypotheses.
 Good descriptive study should answer five basic

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                       The Five Ws

       Ws                                      Components
Who has the disease?           Age, sex, and other characteristics.
What is the condition or       A clear, specific, and measurable case
disease being studied?         definition is essential.
Why did the condition or       Descriptive studies often provide clues about
disease arise?                 cause that can be pursued with more
                               sophisticated research designs.

When is the condition common Time provides important clues about health
or rare?                     events.
Where does or does not the
disease or condition arise?  Geography has a huge effect on health.

          So what? The implicit W relates to the public health effect.
                            Descriptive Studies

              Deal with individual                Relate to the population

 Case report             Cross-sectional
                           prevalence      Ecological cor-relational studies

                I- Case Report
o The least publishable units in the medical literature.
o An observant clinician reports an unusual disease or
  association which prompts further investigations with
  more rigorous study design.
  Example: benign hepatocellular adenoma and high-
    dose contraceptive pills.
o   Not all case reports deal with serious health threats,
    however, some simply enliven the generally drab
    medical literature.

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What is the most probable diagnosis?
              II-Case-series report
A case series report aggregates individual cases in one
Sometimes, the appearance of several similar cases
  heralds an epidemic.
  Example: a cluster of homosexual men in Los Angeles
  with a similar syndrome alerted the medical
  community of HIV/AIDS epidemic in North America.
Case-series report is a major trigger for further
 investigations compared to case report.
Can constitute the case group for a case-control study.
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    III- Cross-sectional (prevalence) Studies.

  Prevalence studies describe the health of populations.
  Examples: Health and Nutrition Examination Survey
  (HNES), and Censuses.
  These studies provide a snapshot of the population at a
  particular time.
  Both exposure and outcome are identified at at one
  point in time.
  Particularly useful for estimating the point prevalence
  of a condition in the population:
                     Number with the disease at a single time point
Point prevalence =
                      Total number studied at the same time point
        Design of a Cross-Sectional Study

                      Defined population
Begin with

               Gather data on exposure and disease

                     Exposed:                        Not exposed:
      Exposed:                    Not exposed:
                    Do not have                      Do not have
     Have disease                 Have disease
                     Disease                           disease

                End with four possible groups
      Cross-sectional (prevalence) Studies.
               Advantages                          Disadvantages

Low  costs.                 Only   association can be inferred “not
No follow up is required.   causation”.
Quick.                      Temporal sequence is difficult to ascertain
                             “exposure-outcome sequence”.
                             Incidence can not be estimated
                             “occurrence of new cases over time”.
                             Trend over time can not be identified
                             “change of magnitude/pattern over time”.

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o   The New Valley Governorate is located in the Western desert
    of Egypt; several reports had described a grade II goiter among
    primary school children, little is known about the prevalence,
    socio-demographic characteristics of the condition.
o   Some clinicians have proposed observing a large number of
    cases of renal failure in the Manzala region at the Northern
    cost of Nile delta, the prevalence and distribution of which
    are lacking.
o   Little is known about the magnitude of extra pulmonary
    tuberculosis in Egypt.
    According to the previous given data give the most
    appropriate study design?
  IV-Repeated cross-sectional studies
        “Longitudinal study”
 Studies that may be carried out at different time points to assess
  trends over time.
 These studies involve different groups of individuals at each
  time point.
 It can be difficult to assess whether apparent changes over
  time simply reflect differences in the group included in
  the study rather in the condition itself.

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               Longitudinal study design.

  Study population            Study population                Study population          Study population

                   Interval                        Interval                      Interval

      Data collection         Data collection                 Data collection         Data collection

1. Maturation effect „maturation of responses in young subjects.
2. Reactive effect „instrument educates the respondents‟
3. Regression towards the mean „shift of extreme attitudes and behavior towards the
4. Conditioning effect „repeated contacting with same persons‟

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                 V- Surveillance
       The ongoing systematic collection, analysis, and
         interpretation of health data essential to the
        planning, implementation, and evaluation of
       public health practices, closely integrated with
         timely dissemination of these data to those
                     who need to know.

Data gathered through the                     Active
 traditional channels e.g.,         Searching and reporting cases.
     death certificates
        VI-Ecological Correlational Studies
   Look for associations between exposures and outcomes
    in the population rather than in individuals.
   Can be a convenient initial search for hypotheses as the
    data are already collected.
   Correlation coefficient r, which indicates how linear is
    the relation between exposure and outcome.
   The mortality of coronary heart disease correlates with
    per capita sales of cigarettes.
 Inverse correlation between access to safe abortion and
    maternal mortality rate.
Consumption of dietary fat and fast food
       in certain community.

                               Ecological study

                                   High mortality from coronary heart disease
                                            (high incidence of MI)
                 Ecological Correlational Studies
    The inability to link exposure to outcome in
    Controlling of confounders.
    are the two major limitations of this type of study.

    Death rates from coronary heart disease is positively
    correlated with number of color television sets per

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VII- Before-and After study design.
     “pre-test/post-test design”
 The most appropriate design for measuring the impact
  of effectiveness of a program.
 Described as a two sets of cross-sectional data
  collection on the same population to find out the
  change in the phenomenon or variables between two
  points in time.
 The change is measured by the difference change
  before and after the intervention.
 It could be experimental or non-experimental.
 Commonly used in evaluation studies.
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  Study population                              Study population


Before/pre observation
   Data collection
   Actual or recall                               Data collection
® Two sets of data collection, more expensive and
  more difficult to implement.
® Time lapse may cause attrition of participants.
® It only measures total change without ruling
  out the role of other variables “confounders”
® Maturation of the response of young
  participants “maturation effect”
® Reactive effect
® Regression effect.
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               Uses of Descriptive Studies

Trend analysis.   Monitor health of the population, provided by ongoing
                   surveillance: epidemic syphilis in USSR, international
                   epidemic of multiple births, prematurity, caused by assisted
                   reproductive technologies.

                   Health services: Laparoscopy, introduction of Anti
                   HIV/AIDS therapy.

Clues about       Development of hypotheses: retrolental hyperplasia, and
cause              painted radium dial watches.
            Descriptive Studies.

           Overstepping of the data:
  Post hoc inference, a temporal association is
  incorrectly inferred to be a causal one.
 Intake of 6 cups of coffee /day is associated with
 lower risk of colonic cancer!!!!

 The role of the media,
 The damage in the control efforts,
 Damage to the public health.
           Research design in relation to time

Exposure                                                        Outcome

Exposure                                Outcome

                       Exposure                                 Outcome

                Finding Your Way in the Terminology Jungle

Case-control study                       =              Retrospective study
Cohort study                 Longitudinal study         Prospective study
Concurrent cohort study      Prospective cohort         Concurrent prospective
Retrospective cohort study   Historical cohort          Non-concurrent prospective
Randomized trial                         =              Experimental study
Cross-sectional study                    =              Prevalence study

   11/14/2010                        Dr. Tarek Tawfik                                165
        Experimental or Observational Study

   Experimental studies involve the investigator intervening in
    someway to affect the outcome.
   Clinical trial is an example of an experimental study in which
    the investigator introduces some form of „treatment, vaccine,
    new surgical procedure, change in the health policy or
    introduction of behavioral interventions‟.
   Other examples include animal studies or laboratory studies
    that are carried out under experimental conditions.
   These studies provide the most convincing evidence for any
    hypothesis as it can possibly control confounders.
     Experimental or Observational Study
   Observational studies „cohort or case-control‟ studies
    are those in which the investigator does nothing to
    affect the outcome, but simply observes what
   These studies provide poorer information than the
    experimental studies because it is often impossible to
    control for all factors that may affect the outcome
   Epidemiological studies which assess the relationship
    between factors of interest and disease in the
    population, are observational.
             Observational (Analytical)

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  Bias and Casual Associations in Observational
            I-Validity and Reliability

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                        Definitions : Validity

*Internal validity: the ability of the tool/test to measure what it sets
   out to measure.
   The inference from participants in a study should be accurate,
   avoiding systematic errors and bias. Wrong extrapolation to the
   general population is potentially dangerous.

** External validity: can results from study participants be
   extrapolated to the reader‟s patients?
    Including the results into the clinical practice.

  Bias in research denotes deviation from the truth.
  (when there is systematic difference between the results from
     study and the truth).
 All observational studies and badly done randomized controlled
      trials have built-in bias.

The most often used classification of bias includes:
I.   Selection bias,
II.  Information bias,
III. Confounding.

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                   I- Selection Bias
     Are the groups similar in all important respects?

     Selection bias stems from absence of comparability
     between groups being studied.

     In a cohort study, are participants in the exposed and
     unexposed groups similar in all important respects except
     for exposure?

     In case-control study, are cases and controls, similar in all
     respects except for the disease in questions?

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                      Selection Bias

              Bias accompanying case-control study:

Berkson bias (admission-rate bias): knowledge of the
    exposure of interest might lead to an increased rate of
    admission to hospital. Admission preference of disease of

Neyman bias (an incidence-prevalence bias): arises when a
  gap in time occurs between exposure and selection of study
  subjects. This bias crops up in studies of diseases that are
  quickly fatal, transient, or sub-clinical.
  Myocardial infarction and its relation to snow shoveling.
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                  Selection Bias
 Unmasking bias:
  An exposure might lead to provoking of an outcome.
  Estrogen replacement therapy and symptomless endometrial

 Non-respondent bias:
  In observational studies, non-respondents are different from
  Smokers are less likely to return questionnaires than are non-
  smokers or pipe and cigar smokers.

 11/14/2010                  Dr. Tarek Tawfik                    176
            II- Information Bias
     Has the information been gathered in the same way?

Also known as observation, classification
 or measurement bias, results from
 incorrect determination of exposure or
 outcome or both.
Information should be gathered in the
 same way in any comparative study.
                     II- Information Bias
              Has the information been gathered in the same way?

 Differentials in information gathering:
 (bedside for cases while using telephone for control).

 Diagnostic suspicion bias:
   (intensive search for HIV in drug addicts).

 Family history bias:
  Medical information flows differently to affected and non-
  affected family members (rheumatoid arthritis).

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             Information Bias

Recall bias: cases are motivated to search their
 memories in order to identify the cause of their
 illness than the healthy people.
Observer bias: one observer consistently under or
 over reports a particular variable. Meticulous
 observation of those who are exposed than the

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             Information Bias control

 Observer and data gatherer should be blinded.
 Using a standardized instruments for data
 Proper selection of the subjects are the possible
  maneuvers to lower the information bias.

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                     III- Confounding.
          Is an extraneous factor blurring the effect?

A confounding variable is associated with the exposure and it
affects the outcome, but it is not an intermediate link in the
chain of causation between exposure and outcome.

Oral contraceptive                       Myocardial infarction


  IUD insertion                                Salpingitis

               Confounding „Control‟
 Restriction (exclusion or specification):
 Enrollment with restricted selection criteria, including non-
 Matching:
 A pair wise matching (for every case who smokes, a control who
  smokes is found).
 Stratification:
 Used after completion of the study. Results can be stratified by
  the levels of the confounding factor.
 Multivariate analysis techniques:
  logistic regression, proportional hazard regression, and others.

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              Judgment of Associations
                Bogus, indirect, or real?
Statistical associations do not imply causal associations.

                       Types of associations:
 Bogus or spurious associations:
  Results of selection, information bias and chance.
 Indirect association:
  Stems from confounding.
 Real associations.

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               Hill‟s Criteria for Real Associations

Temporal sequence:
    Did exposure precede outcome? the cause must antedate the
Strength of association:
   How strong is the effect, measured as relative risk (>3 ) or odds
   ratio (> 1)?
Consistency of association:
   Has effect been seen by others? In different populations with
   different study designs.

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              Hill‟s Criteria for Real Associations

Biological gradient (dose-response relationship):
  Does increased exposure result in more of the outcome?
  Lung cancer and years of cigarette smoking.
Specificity of association:
  Does exposure lead only to outcome?
  “weak criterion, few exposure will only lead to the outcome”.
Biological plausibility:
  Does the association make sense?
  “weak criterion, limited by our lack of knowledge”.

 11/14/2010                    Dr. Tarek Tawfik               185
              Hill‟s Criteria for Real Associations

Coherence with existing knowledge:
   Is the association consistent with available evidence?
   The effect of cigarette smoke on the bronchial epithelium of
   animals is coherent with an increased risk of caner in human.
Experimental evidence:
    Has a randomized controlled study been done?
   Is the association similar to others?

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             Case-control Design
               Research in Reverse

                                          Dr. Tarek Tawfik

11/14/2010                 Dr. Tarek Tawfik                  187
               Examples of Topics Investigated with Case-control Studies

             Exposure                                         Outcome
Cat ownership in childhood           Schizophrenia, schizoaffective disorder, or bipolar disorder
Body mass index                      Pancreatic cancer
Physical disability                  Earthquake mortality
Hiatus hernia                        Reflux oesophagitis
Hair dyes                            Connective tissue disorders
History of shingles                  Systemic lupus eryhtematosus
Pig farming                          Nipah virus infection
Ghee applied to umbilical cord       Neonatal tetanus
Pickled vegetables                   Esophageal cancer
Digital rectal examination           Metastatic prostate cancer
Statins for lipid lowering           Dementia
Paracetamol use                      Ovarian cancer
Phyto-estrogens                      Breast cancer prevention
Male condom use                      Genital warts
Physical activity                    Ovarian cancer
Sigmoidoscopy screening              Colon cancer
Influenza vaccination                Recurrent myocardial infarction prevention
              Case-Control Studies

A   case-control study compares the characteristics of a
  group of patients with a particular disease outcome
  (the cases) to a group of individuals without a disease
  outcome (the control), to see whether any factors
  occurred more or less frequently in cases than the
 Such retrospective studies do not provide information
  on the prevalence or incidence of disease but may
  give clues as to which factors elevate or reduce the
  risk of disease.
 11/14/2010              Dr. Tarek Tawfik             189
                                    Basic structure of case-control design              Population

                                     Exposed to factor
Is calculated between both groups
The Odds “chance of exposure

                                    Unexposed to factor

                                     Exposed to factor

                                    Unexposed to factor                                  Disease-free
                                           (d)                                            (controls)
                                                                    Trace               Present time
         Past time
                                                                                                 Starting point
 Calculate the difference in Odds for
the included exposures for comparison.

 Calculate the difference in Odds for
the included exposures for comparison.
11/14/2010   Dr. Tarek Tawfik   192
Selection of Cases


        Incident cases                       Prevalent cases
  Patients who are recruited           Patients who were already
   at the time of diagnosis        diagnosed before entering the study

                                               1. Recall bias
    1. Less recall bias
                                            2. Altered behavior
 2. Less altered behavior
                                          3. Risk factors may be
3. But, we have to wait to
                                          related more to survival
       be diagnosed
Selection of Cases

                       Patients in Physician‟s
Hospital patients                                      Clinic patients

                    * Single or multiple hospitals;
                    Some hospitals have an aggregation
                    of certain risk factors than others.
                    * Tertiary Health Care Facility;
                    A tendency to select severely ill
                    cases, any risk factors identified
                    may be only found in these severe
                    forms of the disease.
                     Selection of Controls

         Non-hospitalized                                       Hospitalized
             persons                                              persons

     Probability sample          Best-friend control:
                              Similarity in demographic     Captive population:
        School rosters
     Selective service list         Characteristics         They represent a
   Insurance company list         (lifestyle pattern)       sample of ill population.
                                                            Hospital patients are
                                                            differ from people in
                                                            the community.
 Neighborhood controls:       Spouse or sibling controls:
                              Sibling control may provide   A sample of all other
 Door-to-door approach
                               Some control over genetic    patients, admitted
 Or random digit dialing
(Socio-economic, cultural)
                                  Difference between        or to select a specific
                                   Cases and controls       other diagnoses?
             Problems in Controls Selection
   When a difference in exposure is observed between
    cases and controls,
   We must ask whether the level of exposure observed
    in the controls is really the level expected in the
    population in which the study was carried out or
    whether-perhaps (due to the manner of selection)-
    The controls may have a particularly high or low
    level of exposure that might not be representative of
    the level in the population in which the study was
    carried out.

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      Distribution of Cases (cancer pancreas) and Controls by Coffee-
      drinking Habits and Estimates of Risk Ratios

                                             Coffee consumption (cups/day)
Sex         Category             0        1-2           3-4            >5      Total

Male        No. of cases         9         94           53             60        216
            No. of controls     32         119          74             82        307
            Adjusted RR         1.0        2.6          2.3            2.6       2.6
            95 % CI              -       1.2-5.5      1.0-5.3        1.2-5.8   1.2-5.4

Females     No. of cases        11         59           53             28        151
            No. of controls     56         152          80             48        336
            Adjusted RR         1.0        1.6          3.3            3.1       2.3
            95 % CI              -       0.8-3.4      1.6-7.0        1.4-7.0   1.2-4.6
Estimates of Relative Risk of Cancer of the Pancreas Associated
with use of Coffee and Cigarettes

                                  Coffee drinking (cups/day)

                       0            1-2             >5             Total
Cigarette smoking
 Never smoked         1.0            2.1           3.1               1.0
  Ex-smokers          1.3            4.0           3.0               1.3
Current smokers       1.2            2.2           4.6               1.2
Total “RR/95% CI”     1.0            1.8            2.7
                                  (1.0-3.0)      (1.6-4.7)

    The process of selecting controls so that they are similar to
     the cases in certain characteristics, such as age, race, sex,
     socioeconomic status, and occupation.

    To nullify the difference in characteristics or exposures
     other than that has been targeted for study.

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                        Types of Matching

        Group Matching                Individual Matching
          (frequency)                    (matched pairs)
Selection of controls:
Proportion of controls               For every case included
with certain characteristics           an identical matched
identical to proportion of          control should be selected;
cases; 25% of cases are              45 year old white female
married, then 25 % of                case, we seek for 45 year
controls are married.                  white female control.
All cases should be                   used in hospital-based
selected first, and calculation         case-control studies
of proportions are made.
            Problems with Matching

    Practical problems           Conceptual problems
  Matching of too many         Once we have matched controls to
  characteristics is very        cases to a given characteristics,
                                 we can not study that
  difficult or impossible to     characteristics.
  identify an appropriate
  control.                     Marital status and cancer breast, if
A 48-years old black             matching occur as regard
                                 marriage, we can not be able to
  female, married, has 4         study of that factor „marital
  children, lives in zip         status‟. Why?
  code 21209, and work in
  photo-processing plant       Matching ensures the same
                                 prevalence of that characteristic
Find her control?                in both cases and controls.
             Uses of Multiple Controls
  In case-control studies we usually use more than
     one control per case to increase the power of
                       the study.

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    1-Multiple controls of the same type.

The power of the study is increasing by including more controls
   for each case up to 4 controls per case.
Why not keep the ratio of controls to cases 1:1 and just increase
   the number of cases?
1. For many rare disease „cancer, connective tissue disorders‟ the
   number of the cases are limited for study.
2. In addition, with the limited time frame of the study that
   does not allow more inclusion of cases and
3. In the absence of multi-centric collaboration, the option
   remained is to increase the number of controls.

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             2-Multiple Controls of Different Types

         The use of hospital and neighborhood controls:
        To assess the level of exposure among the different
         controls group in relation to the cases.

        Comparing cases with hospital controls, then cases to
         neighborhood controls to assess discrepancy in the
         level of exposure, and if present, the reason should be

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         Nested Case-Control Studies

                    Population           Initial data and/or
                     (Cohort)            specimen obtained

       Develop disease         Do not develop

                  Cases    Selected as
       Advantages of Nested Case-Control Design
Interviews are performed at the beginning of the study
 (baseline), the data are obtained before any disease has develop,
 the problem of possible recall bias is eliminated.
If abnormalities in biologic characteristics are found „specimens
 obtained years before the development of clinical disease‟ , it is
 more likely that these findings represent risk factors or other
 pre-morbid characteristics than a manifestation of early, sub-
 clinical disease.
Temporal association can not be concluded from the ordinary
  case-control design.
More economical to conduct.
 The risk factors for end-stage renal disease are largely
  unknown, describe a study to identify such factors?
 The prevalence of iodine deficiency disorders showed a
  geographic discrepancy between Jeddah and Qaseem, mention
  a design to explore such discrepancy.
 Cross-sectional study reported a difference in the dietary fat
  intake among obese subject, how to confirm such difference?

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             Cohort Study Design

                                           Dr. Tarek Tawfik

11/14/2010              Dr. Tarek Tawfik                      208
                Cohort study
             (marching towards outcomes)

 The term cohort has military, not medical roots.
 A cohort was a 300-600-man unit in the Roman
  army, ten cohorts formed a legion.
 A cohort study consists of bands or groups of
  persons marching forward in time from an
  exposure to one or more outcomes.

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                                               Basic Structure of cohort study

                                                                                     Comparing the incidence of disease in each group
    Disease-free                   The Relative Risk is calculated for exposure

                                                                       Disease (a)


                                           to factor

           Disease-                                                     Develop
             free                                                      Disease (c)
                                          Unexposed                  Disease-free
                                           to factor                     (d)
Present time                                                           Future time
Starting point                           Follow
                                     Incidence of
                                      cancer lung


                                     Incidence of
                                     cancer lung

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                       Exposure                                      Outcome

Exposure   Retrospective


                       Exposure                  Short/long term effects

                      Outcome                                         Outcome
                       Design of Cohort
                         Then follow to see whether             Incidence
                                                                  rate of
                          Disease   Disease does not             disease
                         develops       develop

         Exposed            a              b            a+b        a
select                                                             c
         Not exposed        c              d            c+d       c+d
Data collection in cohort: forwards and backwards

A cohort study follow-up two or more groups from
exposure to outcome.
In the simplest form, it compares the experience of a
group exposed to some factor with another group not
exposed to that factor.
The frequency of the outcome „whether higher or
lower‟ in relation to the unexposed, will gives the
evidence of association between exposure ad outcome.
In general, the cohort should always moves in the
same direction, although the data gathering might not.
  Cohort versus Randomized Trials

Both types compare exposed with non-exposed groups (or a
group with a certain exposure to a group with other exposure).
Because of ethical and other reasons, we can not randomize
people to receive a putatively harmful substance (carcinogens),
the exposure in RCTs is often a treatment or preventive
In cohort studies investigating etiology “exposure” is often to a
toxic or carcinogenic agent.
The difference between the two design is the presence or
absence of randomization which is critical in interpreting the
study findings.
           Selection of Study Population
                Comparison of outcomes in an exposed group
              and non-exposed group (or a group with a certain
                    characteristic and a group without)

                                               Select a defined population before
                                                   any of its members become
Create a study Population by                    exposed or before their exposures
selecting groups for inclusion                      are identified selection by
on the basis of whether or not                    factor not related to exposure
they were exposed                                           (residence),
(occupationally exposed        In both cases we            took histories
cohorts)                         wait for the            or tests and then
                                   outcome            separate into exposed
                                                         and non-exposed
                     Types of Cohort Studies
                     (concurrent prospective)
                           Using a defined population
Concurrent 2000
                     (smoking and lung cancer), population of
                           elementary school children.

                           Non randomized

             Exposed (smoke)                 Non-exposed (non-smoker)

           Disease        No disease             Disease        No disease
     Time frame for a hypothetical concurrent cohort study begun in 2000
                       Types of Cohort Studies
                               Retrospective Historical

                     Defined population (old roster of elementary
Retrospective 1980             School children found)

                            Non randomized                           Surveyed for
                                                                    smoking habit

 1990                                           Non-exposed (non-smoker)
               Exposed (smoke)

2000         Disease         No disease             Disease          No disease

    Time frame for a hypothetical retrospective cohort study begun in 2000
         Advantages of Cohort Design
I.     The best way to ascertain both incidence and natural
       history of a disease (the temporal sequence between the
       putative cause and outcome is usually clear).
II.    Useful in investigation of multiple outcomes that might
       arise after a single exposure (sometimes misleading).
III.   Useful in the study of rare exposures.
IV.    Reduce the risk of survival bias (diseases that are rapidly
       fatal are difficult to study because of this factors).
V.     Allow calculation of incidence rates, relative risks, and
       confidence intervals.
VI.    Other outcome measures include life table rates, survival
       curves and hazard ratios.
                  Potential Biases in Cohort Studies

1)        Bias in assessment of the outcome (blinding or
          masking is used to avoid).
2)        Information bias (particularly in historical or
          retrospective cohort).
3)        Bias from non-response and losses to follow-up
4)        Analytic bias (blinding is needed).

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                  When Is A Cohort study Warranted?

A.        When a good evidence suggests an association of a
          disease with a certain exposure (from clinical
          observations or case-controls or other types of
B.        When are able to minimize attrition of the study
C.        When the interval between exposure and
          development of outcome is relatively short.

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          What To Look For In Cohort Studies
Who is at risk?        All participants in a cohort study must be at risk of
                       developing the outcome.

Who is exposed?        Clear, unambiguous definition of exposure at the outset
                       is required (sometimes quantifying the exposure by
                       degrees, rather than yes/no).

Who is an appropriate
control?              Unexposed should be similar to the exposed in all
                       aspects except for the exposure. Either internal or
                       external sources. The healthy worker effect.

Have outcomes been     Outcomes must be defined in advance; should be clear,
assessed equally?      measurable and specific.
           Reporting of Cohort Studies
   The first table in reports should provides demographic and
    other prognostic factors for both groups with hypothesis testing
    (P value), to show the likelihood that observed differences
    could be due to chance.
   For dichotomous outcome measures (sick/well), provide raw
    data sufficient for the reader to confirm the results.
   For cumulative incidence: calculate the proportion who develop
    the outcome during the specified study interval.
   For incidence rates, the value is expressed per unit of time.
   The relative risks, and confidence intervals should be provided.
     Use of P values should not replace interval
     estimation (relative risk with confidence).
           How to Choose the Study Design?
     Study Design   Selection of   Information    Information
                    subjects by    collected on   collected on
                       status       Exposure        Disease

Cross-sectional         No           Current        Current

Case- Control         Disease         Past          Current

   Prospective      Exposure        Current        Future

   Retrospective    Exposure         Past          Current
            How to Choose the Study Design? (cont.)

       Options       Case-Control   Concurrent   Retrospective
                                      Cohort        Cohort
Study time              Short         Long          Short
Cost                     Low          High           Low
Rare diseases            Yes           No             No
Sample Size             Small         Large         Large
Loss to follow up        No            Yes           Yes

Incidence                No            Yes           Yes
Relative Risk          Approx.         Yes           Yes
             Experimental study
                           Dr Tarek Tawfik

11/14/2010             Dr. Tarek Tawfik      227
  Experimental study designs
                              Experimental studies
   Treatment /                                              Exploration
    Program                             Study                Outcome/
                                      population              Impact/
Causes/associations                                           Change
   Exploration                                                 Effect

                      Non-experimental studies

      Experimental: starts from the cause to effect.
      Non-experimental: starting from the effects to trace the cause.
      Semi (Quasi) experimental: a mix of both.
     The concept of Randomization

             Randomization        Group A         Randomization

       Study             Or                     Or         population

                                  Group B

Any individual or unit of study population has an equal and independent
chance of becoming a part of an experimental or control group, or in the case
of multiple treatment modalities, any treatment has an equal and independent
chance of being assigned to any of the population groups.
             The control group design
                      “the control experimental design”
                                 Independent variable
                                 Experimental group
                Study                                               Study
                                  Intervention arm
              population                                          population     Measuring
Baseline                                                                         dependent
 Data                                                                             variables
                Study              No intervention                  Study
              population          Control group                   population

   The chief objective of the control group is to quantify the impact of extraneous factors
    “possible confounders”, which help to ascertain the impact of the intervention only.
           The placebo design

 A patient‟s belief that is receiving treatment can
  play an important role in recovery from an
  illness even if treatment is ineffective
  “psychological effect known as placebo effect”
 The placebo design attempts to determine the
  extent of this effect.
                  The placebo design

Experimental                        Experimental   Treatment+
   Group        Treatment              Group        Placebo
                  Placebo/                          Treatment+
                confounders                        Confounders
  Placebo         Placebo             Group

                Confounders          Control                     Treatment
  Control                                                        Outcome
                  Control            Group
                                                   Confounders   (-)
       Cross-over comparative design
 Denial of treatment to the control group is considered
 Denial of treatment may be unacceptable to some
  individuals in the control group, which could result in
  drop out of cases.
 The cross-over design experimental design makes it
  possible to measure the impact of a treatment without
  denying treatment to any group.
 Design is based upon the assumption that participants
  at different stages are similar in terms of their
  characteristics and the problem for which they are
  seeking intervention.

11/14/2010               Dr. Tarek Tawfik                  233
        Cross-over experimental design
                        Outcome                    Outcome
              Drug A                     Drug A
                         Non                        Non
                        Outcome                    Outcome
              Placebo                    Placebo
                         Non                        Non



Blind            Blind
             Meta-analysis and systematic

11/14/2010                Dr. Tarek Tawfik   239
             Estimating Risk
                                Dr. Tarek Tawfik

11/14/2010            Dr. Tarek Tawfik             244
                         Absolute Risk
The incidence of a disease in a population is termed absolute risk.
    Can indicate the magnitude of the risk in a group of people with
     a certain exposure, but:
    It does not take into consideration the risk of disease in the non-
     exposed individuals,
    It does not indicate whether the exposure is associated with an
     increased risk of disease.
            Absolute risk doe not stipulate an explicit comparison.
    Rubella in 1st trimester: what is the risk that my child will be
    malformed? Abortion will be decided on the basis of this

    11/14/2010                     Dr. Tarek Tawfik                    245
   Determination that a certain disease is associated
              with a certain exposure.
   By using the case-control and cohort studies we can assess
   whether there is an excess risk of disease in persons who have
   been exposed.

   We have to compare the different risks among different groups
   to assess the presence of excessive risk (by calculating the
   incidence rate „attack rates‟ and the difference in the risks).

   So, estimation of relative risks are vital in determining who
   will be at a higher risk following the exposure.

11/14/2010                    Dr. Tarek Tawfik                     246
                  Relative Risk (concept)
o   Both case-control and cohort studies are designed to
    determine whether there is an association between
    exposure to a factor and development of a disease.
     If an association exists, how strong is it?
o   If we carry out a cohort study, we can put the question
    another way: what is the ratio of the risk of disease in
    exposed individuals to the risk of disease in non-
    exposed individuals? This ratio is called the relative
                   Risk in exposed
Relative risk =
                  Risk in non-exposed
      Interpreting the Relative Risk
       (measure the strength of the association)

If RR = 1     Risk in exposed equal to risk in non-
              exposed (no association).
If RR > 1     Risk in exposed greater than risk in non-
              exposed (positive association; possibly
              Risk in exposed less than risk in non-
If RR < 1     exposed (negative association; possibly
           Calculating the Relative Risk in Cohort
                         Then follow to see whether
                           Disease develops   Disease does not    Totals       Incidence rate of
                                                  develop                      disease
                                  a                    b                             a+b
                                  c                    d                             c
            No exposed                                            c+d

    a        = incidence in exposed                   c
                                                                 = incidence in non-exposed
     a+b                                              c+d
                            Hypothetical Cohort
3,000 smokers and 5,000 non-smokers to investigate the relation of smoking to
    the development of coronary heart disease (CHD) over a 1-year period.

                   Develop CHD        Do not develop          Totals           Incidence per
                                          CHD                                    1,000/year

Smoke cigarettes       84                 2,916                3,000                28.0

 Do not smoke          87                 4,913                5,000                17.4

     Incidence among the exposed=                            Relative risk =
        84/3,000 = 28.0 per 1,000                         Incidence in exposed

                                                       Incidence in non-exposed =
    Incidence among the non-exposed
        = 87/5000 =17.4 per 1,000                           28.0/17.4 = 1.61
             Example: the British Heart Study

 A large cohort study of 7735 men aged 40-59 years
 randomly selected from general practices in 24 British
 towns, with the aim of identifying risk factors for ischemic
 heart disease. At recruitment to the study, the men were
 asked about a number of demographic and lifestyle,
 including information on cigarette smoking habits.
 Of the 7718 men who provided information on smoking
 status, 5899 (76.4 %) had smoked at some stage during their
 lives (including those who were current smokers and those
 who were ex-smokers).
 Over subsequent 10 years, 650 of these 7718 men (8.4 %)
 had a myocardial infarction (MI).

11/14/2010                  Dr. Tarek Tawfik               251
                                             MI in subsequent 10 years

                                  Yes                 No                 Total
Smoking status at baseline
      Ever smoked              563 (9.5%)        5336 (90.5%)            5899

     Never smoked              87 (4.8%)         1732 (95.2%)            1819

          Total                650 (8.4%)         7068(71.6%)            7718

The estimated relative risk=
                                            The middle aged man who has ever
                                            smoke is twice as likely to suffer a
                                            MI over the next 10 years period as
           = 2.00
                                              a man who has never smoked.
      CI = 1.60-2.49
   (does not include 1)
            The Odds ratio (relative odds)
   In order to calculate a relative risk, we must have values for
    the incidence in the exposed and non-exposed, as can be
    obtained in the cohort study.

   In a case-control study, however, we do not know the
    incidence in the exposed population or the incidence in the
    non-exposed population because we start with diseased people
    (cases) and non-diseased people (controls).

   Hence, we can not estimate the RR in case-control study
    directly and we implement another measure of association
    called Odds ratio.
       Defining the Odds ratio in Cohort and in case-
                     control studies.

  Suppose we betting on a horse named Little Beauty, which has a
  60% probability of wining the race (P). Little Beauty, therefore has a
  40 % probability of losing (1-P). What are the odds that the horse
  will win the race?
The odds is defined as: the ratio of the number of ways the event can
  occur to the number of ways the event can not occur.

             Probability that Little Beauty will win the race
Odds =
             Probability that Little Beauty will lose the race
Odds = P/(1-P) or 60 %/40 % = 1.5:1 = 1.5
Probability of wining is 60 %, while the odds of wining is 1.5 times.

11/14/2010                          Dr. Tarek Tawfik                    254
        Odds Ratios in Case-Control and Cohort Studies
 Cohort        Develop       Do not    Case-control         Cases      Controls
               disease       develop
                             disease     History of           a                b
 Exposed           a               b
                                        No history of         c                d
Not exposed        c               d     exposure

              Odds ratio=                               Odds ratio =
     Odds that an exposed person              Odds that a case was exposed
          Develops disease                   Odds that a control was exposed
      Odds that a non-exposed                             = a/c
       Person develops disease
                = a/b
                  c/d                                     = ad
                 = ad                                        bc
    Example: HRT
   A total of 1327 women aged 50 to 81 years with hip
    fractures, who lived in a largely urban area in Sweden,
    were investigated in this un-matched case-controls
    study. They were compared with 3262 controls within
    the same age range selected from the National register.
   Interest was centered on determining whether
    postmenopausal hormone replacement therapy (HRT)
    substantially reduced the risk of hip fracture.
   The results in the table show the number of women
    who were current users of HRT and those who had
    never used or formerly used HRT in cases and
                                  Current users of    Never used HRT/
                                       HRT           former user of HRT
   With hip fracture (cases)         40 (14%)           1287 (30%)          1327

Without hip fracture (controls)         239                3023             3262

            Total                       279                4310             4589

                                                      A postmenopausal woman
                                                     in this age range in Sweden
                                                      who was a current user of
  The observed Odds ratio =                           HRT thus had 39 % of the
          (40X3023)                                    risk of hip fracture of a
         (239X1287)                                  woman who had never used
            =0.39                                       or formerly used HRT
      C.I = 0.28 to 0.56                             Being current user of HRT
                                                      reduced the risk of hip
                                                         fracture by 61%.
   When is the Odds Ratio a Good Estimate of the
                 Relative Risk?
In case-control, only the odds ratio can be calculated as a measure of
association, whereas in a cohort, either the relative risk or the odds ratio is a
valid measure of association.

Nevertheless, estimate of RR can be used in interpreting case-
control study in the following occasions:
When the cases are representative, with regard to history of exposure, of all
people with disease in the population from which the cases are drawn.
When the controls are representative with regard to history of exposure, of all
people without the disease in the population from which the cases were drawn.
When the disease being studied dose not occur frequently.
            Odds Ratios and Relative risk

           Disease       Do not    Total               Develop    Do not    Total
          develops       develop                       disease    develop
                         disease                                  disease
Exposed     200           9800     10,000   Exposed      50         50      100

Not                                         Not          25         75      100
exposed     100           9900     10,000   exposed

           Relative risk=                             Relative Risk =
            200/10,000                                    50/100
          100/10,000 =2                                   25/100
            Odds Ratio=                                     =2
             200X9900                                  Odds ratio =
            100X9800=                                     50X75
                  2.02                                      =3

     The relative odds (odds ratio) is a useful measure of
      association in and of itself, in both case-control and
      prospective studies “Cohort”.
     In a cohort study, the relative risk can be calculated
     In a case-control study, the relative risk cannot be
      calculated directly, so that the relative odds or odds
      ratio (cross-product ratio) is used as an estimate of the
      relative risk when the risk of the disease is low.

    11/14/2010                Dr. Tarek Tawfik              260
   Calculating the Odds ratio in a Matched Pairs Case-
                     Control Study.

   According to the type of exposure, case-control study can be classified into four

                   - pairs in which both cases and controls
   were exposed.
Concordant pairs - pairs in which neither the cases nor the
   controls were exposed.

                   - pairs in which the case was exposed but
   the control was not.
Discordant pairs - pairs in which the control was exposed
   and the case was not.

  11/14/2010                          Dr. Tarek Tawfik                           261
                              2X2 table

     Cases                    Exposed                                Not exposed

   Exposed                        a                                       b
                   Both the case and control were      The case was exposed and the control was
                              exposed                                    not

  Not exposed                     c                                         d
                  The case was not exposed and the        Neither the case nor the control was
                        control was exposed                             exposed

Calculation entail the discordant pairs only (b and c), we ignore
the concordant pairs, because they do not contribute to our
knowledge of how cases and controls differ in regard to past
history of exposure.
                The odds ratio will then equals = b /c
    Case-control study of brain tumors in children.

o    A number of studies have                       Normal control     Total

     suggested that children            Cases     8+ lbs      < 8lbs
     with higher birth weights          8+ lbs      8           18      26
     are at increased risk for
     childhood cancer.                  < 8 lbs     7           38      45

o    In the next analysis,
     exposure is defined as birth       Total      15           56      71
     weight greater than 8 lbs.
                                                  Odds ratio =
                                                  18/7 = 2.57
                                                   2= 4.00
                                                   P = 0.046

11/14/2010                    Dr. Tarek Tawfik                                 263
                 Attributable Risk

 How much of the disease that occurs can be attributed to a
 certain exposure?
 Attributable risk is defined as the amount or proportion of
 disease incidence (or disease risk) that can be attributed to a
 specific exposure.
 How much of lung cancer risk experienced by smokers can be
 attributed to smoking?
 More important than RR as it addresses important clinical
 practice and public health. How much of the risk (incidence) of
 disease can we hope to prevent if we are able to eliminate
 exposure to the agent in question?

11/14/2010                   Dr. Tarek Tawfik                      264
Attributable Risk for the Exposed Group
      Level of risk

                      Exposed    risk
                                 In non

11/14/2010                                Dr. Tarek Tawfik   265
  Incidence due
  to exposure

Incidence not due
to exposure

                    In exposed   In the non-
                    group        exposed group
The incidence of a disease that is attributable to the exposure in the exposed
   group can be calculated as follow:

(incidence in   the exposed group) - (incidence in the non-exposed group)

Then, what proportion of the risk in exposed persons is due to the exposure?
(incidence in the exposed group) - (incidence in the non-exposed group)

                incidence in the exposed group

11/14/2010                          Dr. Tarek Tawfik                             267
Attributable Risk for the Total Population
    What proportion of the disease incidence in a total population (both exposed
    and non-exposed) can be attributable to a specific exposure?
What would be the total impact of a prevention program on the community?

Calculations entail:
(Incidence in the total population) – (incidence in non-exposed group „background risk‟).

In proportion:
(Incidence in the total population) – (incidence in non-exposed group „background risk‟).
                  Incidence in total population

11/14/2010                               Dr. Tarek Tawfik                                   268
 Example for calculating the attributable risk in the exposed group

  Smoking status    Develop CHD    Do not develop     Total    Incidence per 1,000 per
                                       CHD                              year

 Smoke cigarettes        84            2,916         3,000              28.0
  Do not smoke
                         87            4,913         5,000              17.4

               Incidence among smokers = 84/3,000 = 28.0 per 1,000
             Incidence among non smokers = 87/5,000 = 17.4 per 1,000
The AR = (incidence in exposed group) – (incidence in the non exposed group) = 28.0
                           – 17.4 /1,000 = 10.6 /1,000????
   In proportion = The AR = (incidence in exposed group) – (incidence in the non
                   exposed group) /( incidence in exposed group)
                = 28.0 – 17.6/ 28.0 = 10.6/28.0 = 0.379 = 37.9 %?????
    What does this mean?
    The attributable risk = 10.6 /1,000, it means that 10.6 of the
     28.0/1,000 incident cases in smokers are attributable to the fact
     that these people smoke.

    Thus if we had an effective smoking cessation campaign, we
     could prevent 10.6 of the 28/1,000 incident cases of CHD that
     smokers experience.

    In proportion, 37.9 % of the morbidity from CHD among
     smokers may be attributable to smoking and could presumably
     be prevented by eliminating smoking.

    11/14/2010                   Dr. Tarek Tawfik                     270
                 Attributable risk in total population

    The incidence in the total population can be calculated by
    subtracting the background risk.
     (incidence in the total population) – (incidence in the non-exposed group),
      calculation we must know the incidence of the disease in the
      total population (which we often do not know), or all of the
      following three values, from which we can then calculate the
      incidence in the total population:
     The incidence among exposed.
     The incidence among the non-exposed.
     The proportion of the total population that exposed (frequently
      assumed or judged).
    11/14/2010                           Dr. Tarek Tawfik                          271
                    AR in total population.

   Assuming that the incidence in the total population of smoking
    is 44% (and therefore the proportion of non-smokers is 56%).
   The incidence in the total population can then be calculated as
    (incidence in smokers)(% of smokers in the population) +
    (incidence in non-smokers)(% of non-smokers in population).
     = (28.0/1,000)(0.44)+(17.4/1,000)(0.56)= 22.1/1,000
    Then the AR= 22.1/1,000 – 17.4/1,000 = 4.7/1,000.
   It means that, if we an effective prevention program, how
    much reduction in the incidence of the CHD could be
    11/14/2010                       Dr. Tarek Tawfik            272
    AR in total population
     Proportion of incidence in the total population =
      (incidence in the total population) – (incidence in the non-
      exposed group)/ incidence in the total population = 22.1-
      17.4/22.1= 21.3%.

     Thus, 21.3 % of the incidence of CHD in this total population
      can be attributed to smoking, and if an effective prevention
      program eliminated smoking, the best we could hope to
      achieve would be a reduction of 21.3 % in the incidence of
      CHD in the total population which consisting of both smoking
      and non-smoking.

    11/14/2010                   Dr. Tarek Tawfik                    273
              Clinical Trials
             An introduction
                                      Dr. Tarek Tawfik

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   What is a Clinical Trial?
             A prospective study comparing the
             effect and value of intervention (s)
             against a control in human being.
       Friedman, 1998

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             Hierarchy of Medical Evidence

From weakest to strongest evidence:
     Case report.
     Case series.
     Database studies.
     Observational studies.
     Controlled clinical trials.
     Randomized controlled trial (RCTs).
Leon Gordis 2001.

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Randomized Controlled Clinical Trail
   The gold standard of research

    Level of evidence



                         Case reports, case series, and
                               database studies
             Intervention studies (Clinical Trials)
     In an intervention study, the investigator determines
     which individuals are exposed to the factor of interest
     (intervention arm) and which are unexposed (control

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             Essential Elements of RCTS
   Properly designed.
   Unbiased treatment assignment
   Comparable test groups “similar baseline
   Intervention and control arms.
   Follow-up for a specific outcome.

11/14/2010               Dr. Tarek Tawfik     279
                    Types of RCTS

         Treatment trials.
         Preventive trials (vaccine).
         Diagnostic or screening tests.
         Trials of health care delivery.
         Trials of health care policy.

11/14/2010               Dr. Tarek Tawfik   280
Types of Treatment Trials
  Pharmaceutical (treatment,
  prevention, biological, synthetic).
  Device (prosthesis, sensory aids).
  Procedure (surgery, laser,
  Behavior change (smoking cessation,
  dietary modification, exercise).
  Other (counseling, information
11/14/2010          Dr. Tarek Tawfik   281
       Pharmaceutical Development

11/14/2010         Dr. Tarek Tawfik   282
Clinical Trials Phases – Phase I
Purpose: determine basic safety and pharmacological
I.   Route of administration.
II.  Safe dosage range.
III. Toxicity.
IV.  Pharmacokinetics.
oTreat:       small numbers of patients over short period of
oUsually       no control group
oHealthy adult volunteers or patients who have
exhausted all other options (terminal cancer patients)
 11/14/2010                    Dr. Tarek Tawfik           283
Clinical Trials Phases – Phase II
Purpose: evaluate the drug in patients who
  suffer from the disease or condition that the
  drug is proposed to treat:
  Provide preliminary evaluation of
  Identify group of patients most likely to
  Collect additional dosage and safety
  Usually comparison group but not
  always randomized.
11/14/2010                     Dr. Tarek Tawfik   284
Clinical Trials Phases – Phase III

Purpose: further evaluate the efficacy and safety:
⌂   New agent compared to placebo or current
⌂   Usually multi-centeric.
⌂   Serve as basis for NDA i.e. new drug
    application for marketing approval.

11/14/2010                     Dr. Tarek Tawfik   285
    Clinical Trials Phases – Phase IV

    Drug is on the market – post surveillance
    Purpose: collect longer term data on safety
     and efficacy and identify an advantage over
     other therapies.
    Conducted for the approved indication, but
     may evaluate different doses or effects of
     extended therapy.

11/14/2010                       Dr. Tarek Tawfik   286
Outcomes of Trial Phases

o Phase I : maximum tolerated dose.
o Phase II : biological effect, adverse
o Phase III : efficacy, adverse events.
o Phase IV : long term effectiveness and

11/14/2010        Dr. Tarek Tawfik        287
             Measures For Bias Control
☻ Written protocol.
☻ Tested data collection forms, handbooks,
  manuals of procedures.
☻ Written definitions.
☻ Standard equipment.
☻ Training and certification of personnel.
☻ Independent data entry.

11/14/2010            Dr. Tarek Tawfik       288
 Reference population
    Sampling (Random)      Sampling procedures

Experimental population   Unwilling

     selection criteria

 Study population
    RCTs “Basic Structure”
              Reference population
                       Random sampling
              Sample population


   Control                      Intervention

Outcome   No outcome        Outcome No outcome
              Control arm
WHY? ☻Spontaneous cure ☼ Side
HOW? ⌂ Criteria ► Historical

11/14/2010        Dr. Tarek Tawfik   291
Examples of control arm
 Standard care.
 Placebo.

 Careful follow-up.

 Early or late application of same
 Higher or lower dose level.

11/14/2010          Dr. Tarek Tawfik   292

o Meansthat subjects recruited from the study
population are allocated to either intervention or
control arm by chance.
o Random         procedure ≠ haphazard procedure

  11/14/2010                  Dr. Tarek Tawfik     293
       Why Randomization

o Ensures comparability of the two arms
 regarding known and unknown factors.
o Avoid selection bias.
o Provides basis for standard statistical
oDifferences in baseline characteristics of the
 study arms indicate break in randomization.

11/14/2010           Dr. Tarek Tawfik         294
Why Randomization is difficult?
    Any randomization technique must
    Every new subject has an equal
    chance to be allocated to either
    arms (alternation?!)
    Nearly equal number of
    subjects in each arm (coin
11/14/2010           Dr. Tarek Tawfik   295
     Randomization Techniques

 I- Fixed allocation randomization:
☺ Simple randomization.

☺ Blocked randomization.

☺ Stratified randomization.

II- Outcome adaptive designs:
☻     Play the winner.
III- Others.
11/14/2010            Dr. Tarek Tawfik   296
         Simple randomization

            Sealed envelopes.
            Random number tables.
            Computer generated.

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      Blocked Randomization

I.           Blocks containing specific number of participants
             are generated (5 blocks, each containing 4
             participants for a study with total of 20
II.          Within each block, participants are randomly
             allocated to either arms.

  C          T    C   T    T   T       C          C     C C T   T

              T   C C T                        T      C T   C

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Stratified randomization

11/14/2010       Dr. Tarek Tawfik   299
             Baseline measurements

Useful to check that comparability
 has been successfully achieved.

11/14/2010            Dr. Tarek Tawfik   300
             Design of the trial
Methodology section should include the
I. Patient inclusion criteria.
II. Time of patients inclusion in the
III.Presence of a comparison group.
IV. Matching criteria of the two groups.
V. Method used for randomization.

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 Means ensuring that a person
 “investigator, data collector, or
 analyst” remains unaware of which
 arm a subject has been allocated to.

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                          Why Blindness?
I.            To reduce selection bias.
II.           To avoid bias in outcome measures.

Blinding is not possible in all studies so, one
    needs to consider how important it is, and
    to what extent it can be achieved.

      11/14/2010                    Dr. Tarek Tawfik   303
 Trials are often described as:
 o Single-blind: the subject participating in the
 o Double-blind: the subject & investigators
       (clinician, interviewers, laboratory personnel).
 o Triple blind: the subject, investigators & the
       committee (including data entry and analysis)
       responsible for monitoring outcome.

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             Procedures to be considered

  Compliance of the subjects can be
       assessed by:
  I. Questioning
  II. Observing
  III. Check drug
  Completeness of follow-up.

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   Complex designs
       1- Multiple treatment groups
  More than 2 different treatments (or doses)
             may be compared with a control group.

                      Sample population

   Control         Drug A         Drug B       Drug C

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    Complex designs

               2- Cross-over trial
o Each subject receives both the active
o and control treatments during two periods
  separated by a wash-out period.

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               Enrolled population

    Placebo                    Drug A

 Outcome   No outcome      Outcome   No outcome

              Wash-out period

     Placebo                    Drug A

Outcome    No outcome     Outcome    No outcome
    Complex designs
                  3- Factorial design
    Used to evaluate the separate and combined
     effects of two different factors:
    Group 1: Placebo.
    Group 2:. Iron
    Group 3: Folate.
    Group 4: Iron + Folate

                   Sample population

Control Surgery       Radiotherapy      Surgery+Radio
        Losses to follow-up (Attrition)
1)    One of the most important sources of
      bias, since those lost may be different
      from those seen.
2)    Compare drop-outs to non-drop-outs.
3)    Perform sensitivity analysis.

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Interpretation of trial

1- Reporting the data.
2- Statistical methods.                 P < 0.05 ??

3- Statistical analysis.
4- Power.

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    Good RCT should report
   Clear definition of patients.
   Comparison group.
   Randomization and blindness.
   Outcome criteria and variables.
   Compliance and completeness.
   Complications of treatment.
   Statistical manipulation.

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             Sample Size Calculation

    Standard formulae and look-up tables
     are available to calculate the minimum
     sample size and ratio of controls to

    Some computer packages (Epi-Info,
     MedCalc) are also available for free
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             Ethical Issues In RCT
                  The Belmont Report
Ethical Principles and Guidelines for the Protection of
Human Subjects of Research.
It sets the fundamental ethical principles underlying
acceptable conduct of research involving human
                 • Respect for persons
                    • Beneficence
                       • Justice

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             Critical Appraisal of
              Published Medical
                   Dr. Tarek Tawfik

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                                                      Steps in evaluation of a published paper
              Consider the research hypothesis

                  Consider the study design

               Consider the outcome variable

               Consider the predictor variables

               Consider the methods of analysis

             Consider the possible source of bias

             Consider the interpretation of results

               Consider the utility of the results

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 Stepwise Approach for Appraisal.
             Step 1. Consider the research hypothesis

     Is there a clear statement of the research
     Does the study address a question that
     has clinical relevance?

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Step 2. Consider the Study
   Is the study design appropriate for the
   Does the design represent an advance over prior
   Does the study use an experimental or an
   observational design?

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    Step 3. Consider the Outcome Variable

     Is the outcome being studied relevant to
     clinical practice?
     What criteria are used to define the presence
     of disease?
     Is the determination of the absence or presence
     of disease accurate?

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Step 4. Consider the Predictor Variable
     How many exposures or risk factors are being studied?
     How is the presence or absence of exposure
     Is the assessment of exposure likely t be precise and
     Is there an attempt to quantify the amount or duration
     of exposure?
     Are biological markers of exposure used in the study?

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Are the Consider the Methods of Analysis
Step 5. statistical methods employed suitable for
 the types of the variables (nominal versus, ordinal
 versus continuous) in the study?
 Have the levels of type I and type II errors has been
 discussed appropriately?
 Is the sample size adequate to answer the research
 Have the assumptions underlying the statistical tests
 been met?
 Has chance been evaluated as a potential
 explanation of the results?
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Step 6. Consider Possible source of Bias
(Systematic Error)
 Is the method of selection of subjects likely to
 have biased results?
 Is the measurement of either the exposure or
 the disease likely to be biased?
 Have the investigators considered whether
 confounders could account for the observed
 In what direction would each potential bias
 influence the results?
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  Step 7. Consider the interpretation of the
 How large is the observed effect?
 Is there evidence of a dose-response relationship?
 Are the findings consistent with laboratory
 Are the effect are biologically plausible?
 If the findings are negative, was there sufficient
 statistical power to detect an effect?

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    Step 8. Consider how the results of the
        study can be used in practice.

     Are the findings consistent with other studies
     of the same questions?
     Can the findings be generalized to other
     human populations?
     Do the findings warrant a change in current
     clinical practice?

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                                Thank you

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