This book examines how individuals behave across time and to what degree that behavior changes, fluctuates, or remains stable. It features the most current methods on modeling repeated measures data as reported by a distinguished group of experts in the field. The goal is to make the latest techniques used to assess intraindividual variability accessible to a wide range of researchers. Each chapter is written in a "user-friendly" style such that even the "novice" data analyst can easily apply the techniques. Each chapter features: a minimum discussion of mathematical detail; an empirical example applying the technique; and a discussion of the software related to that technique. Content highlights include analysis of mixed, multi-level, structural equation, and categorical data models. It is ideal for researchers, professionals, and students working with repeated measures data from the social and behavioral sciences, business, or biological sciences.
Author(s): D. S. Moskowitz, Scott L. Hershberger, D.S. Moskowitz
Edition: 1
Year: 2001
Language: English
Pages: 296
Contents......Page 8
Preface......Page 10
1 Traditional Methods for Estimating Multilevel Models......Page 18
2 Alternative Covariance Structures for Polynomial Models of Individual Growth and Change......Page 42
3 Structural Equation Modeling of Repeated Measures Data: Latent Curve Analysis......Page 76
4 Multilevel Modeling of Longitudinal and Functional Data......Page 104
5 Analysis of Repeated Measures Designs with Linear Mixed Models......Page 120
6 Fitting Individual Growth Models Using SAS PROC MIXED......Page 152
7 Multilevel Modeling of Longitudinal and Functional Data......Page 188
8 Times Series Regressions......Page 220
9 Dynamic Factor Analysis Models for Representing Process in Multivariate Time-Series......Page 252
D......Page 284
K......Page 285
R......Page 286
Z......Page 287
F......Page 290
M......Page 291
R......Page 292
W......Page 293
