EPID 766: Analysis of Longitudinal Data from ... - NCSU Statistics

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TABLE OF CONTENTS Epid 766, D. Zhang Contents 1 Review and introduction to longitudinal studies 3 1.1 Review of 3 study designs . . . . . . . . . . . . . . . . . . 3 1.2 Introduction to longitudinal studies . . . . . . . . . . . . . 9 1.3 Data examples . . . . . . . . . . . . . . . . . . . . . . . . 10 1.4 Features of longitudinal data . . . . . . . . . . . . . . . . 18 1.5 Why longitudinal studies? . . . . . . . . . . . . . . . . . . 20 1.6 Challenges in analyzing longitudinal data . . . . . . . . . . 23 1.7 Methods for analyzing longitudinal data . . . . . . . . . . 28 1.8 Two-stage method for analyzing longitudinal data . . . . . 29 1.9 Analyzing Framingham data using two-stage method . . . 31 2 Linear mixed models for normal longitudinal data 46 2.1 What is a linear mixed (effects) model? . . . . . . . . . . 47 2.2 Estimation and inference for linear mixed models . . . . . 63 2.3 How to choose random effects and the error structure? . . 65 Graduate Summer Session in Epidemiology
TABLE OF CONTENTS Epid 766, D. Zhang 2.4 Analyze Framingham data using linear mixed models . . . 66 2.5 GEE for linear mixed models . . . . . . . . . . . . . . . . 102 2.6 Missing data issues . . . . . . . . . . . . . . . . . . . . . 106 3 Modeling and design issues 111 3.1 How to handle baseline response? . . . . . . . . . . . . . . 112 3.2 Do we model previous responses as covariates? . . . . . . 114 3.3 Modeling outcome vs. modeling the change of outcome . . 116 3.4 Design a longitudinal study: Sample size estimation . . . . 126 4 Modeling discrete longitudinal data 133 4.1 Generalized estimating equations (GEEs) for continuous and discrete longitudinal data . . . . . . . . . . . . . . . . 134 4.1.1 Why GEEs? . . . . . . . . . . . . . . . . . . . . . 134 4.1.2 Key features of GEEs for analyzing longitudinal data138 4.1.3 Some popular GEE Models . . . . . . . . . . . . . 140 4.1.4 Some basics of GEEs . . . . . . . . . . . . . . . . 142 4.1.5 Interpretation of regression coefficients in a GEE Model . . . . . . . . . . . . . . . . . . . . . . . . 148 Graduate Summer Session in Epidemiology
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