E P I809 S Y L L A B U S2008 by 26Nb3u

VIEWS: 37 PAGES: 2

									EPI 809 Biostatistics II
SPRING 2008

Instructors:   Wenjiang Fu, PhD, Office: B-626 West Fee Hall, Office phone #: 353-8623 Ext. 113
               E-mail: fuw@msu.edu http://www.msu.edu/~fuw

Class Meets:   MW 4:10-5:30pm. EPI classroom A131 East Fee Hall or Computer Lab B217 Bessey Hall
               (to be discussed on the first day of class)

Office hours: 3:00 pm – 3:30 pm and 5:30 pm – 6:00 pm. Mon and Wed.


Prerequisites: EPI 808, EPI 851

Text:          Rosner, B. Fundamentals of Biostatistics, 6th Edition, Duxbury. You should have this textbook
               from your Fall 2007 EPI 808 course.

Course:        EPI809 should be useful to a wide variety of students both as preparation for more advanced
               courses and as a means to professional advancement. Throughout your life, you will need to
               make judgments based on data. This class is designed to help you in this regards. If you ever
               wanted to answer questions like: “Is there any relationship between high salt intake and the
               occurrence of death from cardiovascular diseases?” or “How well does an experimental
               ointment in reducing excessive redness in people who cannot otherwise be exposed to
               sunlight?”, then this class will help. Tools from statistics can help you rule out competing
               theories and judge the strength of relationships. It is not just about “the numbers” but rather
               thinking clearly about what data do and do not imply.

               This course is the continuation of EPI 808 addressing topics in statistical inference at an
               introductory level. Material will be selected from Chapters 9-13 (from the Rosner’s 6th edition).
               Some sections will need additional material that will be supplied. The emphasis in the text and
               in the examples is biostatistical application. Note the references in the Index of Applications to
               several areas in the Health Sciences. The exercises at the end of each chapter are usually direct
               applications of theory discussed earlier, some of which can be done on a calculator while others
               need computer assistance with statistical software.


Computer use Several data sets from actual research studies are supplied on a CD-ROM with your textbook.
             We will analyze a selection of these using SAS software. The emphasis of the lab session will
             be on statistical procedures, rather than data management. You may use the lab at anytime
             when it is not being used for classroom instruction. Check the availability of SAS software in
             computer labs elsewhere on campus. SAS site license (single year) is available from MSU
             computer store at student discount price.

               SAS is one of the comprehensive software packages available today for statistical analysis. Its
               use is widespread in government and industry, especially in the pharmaceutical industry, NIH,
               the FDA and in almost all clinical research institutions, both public and private. You have
               already gained some experience with the system through the SAS Workshop (EPI 851) that was
               conducted in the fall semester (which continues this semester with EPI 852).
Grading       There will be two quizzes (20%), 1 mid-term exam (20%), and a final exam (40%). There will
              be no make up exams or quizzes. We will have regular homework assignments (20%) using the
              exercises at the end of each Chapter. You are also expected to do and hand in homework on due
              dates. You will need to use the computer to work on some of these assignments. Quizzes will
              be in a multiple-choice format.

                               TENTATIVE COVERAGE FOR EPI809


                                 PART 1 (Continuous response models)

Chapter 11:   Linear regression models; Estimation and testing of regression parameters; Goodness-of–fit;
              Correlation; Multiple regression; SAS PROC REG; SAS PROC GLM.

Chapter 12:   Comparison of means for several samples; Fixed effects one-way ANOVA; Linear contrasts;
              Multiple comparisons; Bonferroni and Scheffé methods; Two-way ANOVA; Regression and
              ANOVA; Analysis of covariance; SAS PROC ANOVA;

                                  PART 2 (Non-parametric methods)

Chapter 9:    Nonparametric methods; The Wilcoxon rank-sum test; The Sign-test; The Wilcoxon Sign-rank
              test.

                                 PART 3 (Categorical response models)

Chapter 10:   Comparison of binomial proportions; Contingency tables; Fisher’s test; Matched-pair studies;
              McNemar’s test; Sample size and power for comparing proportions; Test for trend in
              proportions; Goodness-of-fit; Kappa statistic; SAS PROC FREQ.

Chapter 13:   Study designs; Odds ratios, relative risk, risk difference; Confounding and Stratification;
              Mantel-Haenszel test; Effect modification; Estimation of odds ratio in matched studies.
              Introduction to logistic regression; SAS PROC LOGISTIC.



Notes:        The first two parts of the course divide approximately into the analysis of continuous data
              (chapters 9, 11, 12) and categorical data (chapters 10, 13). This coverage may be too ambitious
              given the need to spend some time getting accustomed to SAS. Handouts where needed for
              various sections will be provided to keep us at a steady pace.

              There is no class meeting on Martin Luther King Holiday (Jan 21) and throughout Spring break
              (Mar. 3 – 7).

Tentative schedule of quizzes/exams

QUIZ 1: Monday - Feb 4
MID TERM EXAM: Monday - Mar 10
QUIZ 2: Wednesday - Apr 2
FINAL EXAM: Wed - April 30 5:45pm – 7:45 pm.

								
To top