# Surveys and Population-Based Studies by 9riGqrvL

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```									Surveys and Population-Based Studies
   Definition of a "Survey"
A method of collecting information about a human
population in which direct (or indirect) contact is made
with the units of the study (e.g., individuals,
organizations, communities, etc.) by using systematic
methods of measurements like questionnaires and
interview schedules. (Warwick and Lininger, 1975)
   Examples of well-known surveys:
– U.S. Decennial Census
– Current Population Survey (n=60,000 HHs/mo.)
– Health Interview Survey (n=50,000 HHs/yr.)
– Other Examples in Groves, et al. (2004)

1
Nonprobability Sampling
 Selection by nonrandom methods
 Membership in the sample is ultimately left
to human judgment
 No basis for assuming stochastic behavior
of sample estimates
 One method: quota sampling

2
Quota Sampling
 Quota control/allocation for each interviewer:
Interviewer
Category   Age    Gender   Assignment
1       <40      M          15

2       <40      F          15

3       >40      M          10

4       >40      F          10

TOTAL        50

 Filling category is left to interviewer's discretion (i.e., judgment)

3
Probability Sampling
 Ultimate   selection left to some randomized
(i.e., chance) mechanism
 Two types:
– Random sampling
– Survey sampling

4
Random Sampling
 "Population"  is infinite and abstract;
distribution of measurements follows some
assumed form (e.g., a normal distribution)
 Sample is the result of independently
selecting a measurement at random from the
assumed distribution, with sample size as
the number of selections

5
Random Sampling
 “Random sample” as defined by Hogg & Craig:
 "Let X1, X2, . . ., Xn denote n mutually statistically independent
random variables, each of which has the same but possibly
unknown probability density function, f(x). The random variables
X1, X2, . . ., Xn are then said to constitute a random sample from
a distribution that has pdf, f(x).
 Example: f(x) for the normal distribution:

f (x) 
1
exp 
L
( x   )2
M            O
P        x  
2  2
N  2 2      Q

6
Population-Based Sampling
 Population is finite (i.e., made up of a
countable set of members)
 Distribution of measurements usually does
not follow a neat mathematical form
– Ex: Number of health care visits in the past 12
months
 Randomization used but selections may not

7
Probability Sampling
 Each population element has a known and nonzero
probability of being selected into the sample
 EPSEM sample design:
– Sample in which selection probability for each
element is equal;
– Stands for Equal Probability Selection Method.
– Also use the term "self-weighting"

8
Sampling
 Statistical theory (including sampling
theory) assumes this method
 Not subject to biases of human judgment
 Can directly measure the precision (i.e.,
statistical quality) of estimates produced
from sample

9
Utility of Sampling Theory
 Basis for settling on ways to estimate
population parameters and the precision of
those estimates
 Basis for much of the decision making in
designing the sample

10
Inference in Population-Based Studies
 Circle    of inference:      Population:
Values to be
Estimated

Analysis:                                   Sample Design
(Population Values                           (Probability Sampling)
Estimated)

Selected Sample:
(Data Collected)
11
Population Hierarchy
Population

Member
12
Population Hierarchy: Some Examples
 First   grade students in NC schools

 Residents   of the United States

13
Components of a
Population-Based Study
 Planning
– Study specifications
   Target population
vs.
   Survey population
– Budget considerations
– Staff communication
– Sample size

14
Components of a
Population-Based Study
 Sampling
– Preliminary activities
– Search for sampling frame(s)
   List(s) of units to be sampled
– Develop the sample design
 Plan to choose the sample
 Consists of a sequence of statistical issues and
decisions
– Select the sample

15
Components of a
Population-Based Study
   Data collection instrument
– Design questionnaire and forms
– Small-scale testing
– Manuals for training
   Data collection
– Preparation (e.g., hiring and training)
– Field operations (e.g., monitoring and supervision)
   Manual editing/coding
– Preparation
– Operations

16
Components of a
Population-Based Study
 Data   entry
– Preparation
– Operations
 Machine    editing/coding and file processing
– Preparation
– Run edits
– Prepare analysis work files
 Analysis   and dissemination

17

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