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Drexel University School of Public Health

PBHL 625Longitudinal Data Analysis

(3 credit hours)

Instructor: Zekarias Berhne, Ph.D

Dept. of Epidemiology and Biostatsitics

Drexel University

6th Floor, Office 652 3215MarketSt., Philadelphia, PA 19104

E-mail: zb26@drexel.edu

Phone: (267) 359-6035

Course Time: Tuesday 9:00AM 11:50AM

Course Location:

NESBITT132

Office Hours: TBD

COURSE DESCRIPTION:

Longitudinal data measure characteristics on the experimental units repeatedly over time. Itis an essential design to study temporal change and to est ablish causal relationships. Theanalysis of longitudinal data, however, requires much more sophisticated methodologies dueto the correlation intro duced by repeated measurements. This co urse covers modernstatistical techniques for longitudinal data fro m an applied perspect ive. Topics includecharacteristics of the lo ngitudinal design, graphical exploration of the mean and correlationstructure, ANOVA for repeated measurements, general linear model, linear mixed effectsmodels, maximum likelihood and restricted ma ximum likelihood estim ation, modeling thevariance-covariance structures, inf erence for random eff ects, logistic and Poisson mixedeffects model for binar y and count data, marginal models and ge neralized estimatingequations, model diagnostics and missing da ta handling. Analysis of real and substantialdata sets using statistical software SAS will be integrated throughout.

The course is suitable for master students in biostatistics and doctoral students in other fieldssuch as epidemiology or the social sciences who need to analyze longitudinal data.

COURSE OBJECTIVES:

The students will learn to do the following:

1. Identify the special features of longitudinal design, describe how these features mightrelate to the analysis. Manipulate the data in a way suitable for longitudinal analysis.

2. Graphically explore and present the longitudinal data.

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3. Use SAS Proc mixed to analyze continuous longitudinal data. Correctly specify fixed andrandom effects and covariance structure. Interpret the SAS output.

4. Use SAS Proc genmod to analyze repeated binary or count data using generalizedestimating equation techniques.

5. Use SAS Proc Glimmix to perform logistic and Poisson mixed effects modeling forrepeated binary or count data.

6. Predict the impact of missing data on standard statistical inference and for a particularsituation, be able to choose between the common approaches for handling missingvalues.

7. Plan and design a longitudinal study. Use an appropriate method to analyze a particularstudy and interpret the result.

8. Use the above methods to analyze other correlated data such as multi-center clinical

trials.

PREREQUISITES:

PBHL620 Intermediate Biostatistics I.

TEXTBOOKS:

Required:

Garrett Fitzmaurice, Nan Laird, James Ware:Applied Longitudinal Analysis 2ndEd, WileySeries in Probability and Statistics,2011.ISBN: 978-0-470-38027-7

Recommended:

Hellen Brown, Robin Prescott: Applied Mixed Models in Medicine, Statistics inPractice,2006.ISBN: 0470023562

Peter Diggle, Patrick Heagerty, Kung-Yee Liang, Scott Zeger:Analysis of Longitudinal data,Oxford Statistical Science Series, 2002.ISBN 0198524846

COURSE FORMAT:

A session usually consists of 2 hours of lecture and 50 minutes of computer lab. There willbe 6 homework assignments. Students are encouraged to work together on assignments butthe final write-up must be each individual's work. Both midterm and final exams will be closedbook but a two page formula sheet is allowed. For students in full-time School of PublicHealth degree programs, SAS software can be obtained from the School of Public Healthlibrarian. Students with issues accessing SAS software should contact Georgeanne Talarico(glt23@drexel.edu) in the Epidemiology and Biostatistics Department.

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GRADING:

10% based on attendance and participation, 40% based on homework assignments and50% based on midterm and final exams. Homework are due at the beginning of each class a

week from the assignment date.

COURSE SCHEDULE:

Week Topic ReadingAssignment *

HomeworkGiven

HomeworkDue

1 Introduction to longitudinal studies,design considerations

Chapter 1, 2

2 Graphical exploration andpresentation of longitudinal data,

repeated measure ANOVA,overview of linear models forlongitudinal data, SAS Procglm/mixed

Chapter 3 HW 1

3 General linear model forlongitudinal data, SAS Proc mixed

Chapter 4,5,6 HW 1

4 General linear model forlongitudinal data, SAS Proc mixed

Chapter 7 HW 2

5 General linear mixed model forlongitudinal data, SAS Proc mixed

Chapter 8,9 HW 3 HW 2

6 Review for the midterm exam HW 37 Midterm Exam, generalized linear

model

Chapter 11

8 Generalized linear models,marginal models and GEE, SASProc Genmod

Chapter 12,13 HW 4

9 Generalized linear mixed effectsmodels, SAS Proc glimmix

Chapter 14,15 HW 5 HW 4

10 Contrasting marginal and mixedeffects models, missing values inlongitudinal data

Chapter 16-18 HW 5

11 Final Exam

* This is for Garrett Fitzmaurice, Nan Laird, James Ware (2ndEd, 2011)Applied LongitudinalAnalysis.