Modeling Intraindividual Variability With Repeated Measures Data

Scott L. Hershberger, D.S. Moskowitz

"...a 'good-to-read' book for all researchers who are interested in analyzing repeated measures data in general and a 'must-read' book for those interested in modeling intraindividual variability in particular, be it in their actual substantive research or in teaching others in the classroom...the chapters in the book provide an important contribution in terms of bridging the gap between advances in repeated-measures data analysis and the current knowledge levels (on these techniques) of the majority of researchers in the wide variety of social and behavioral sciences who are not methodological experts."—Organizational Research Methods"There is evidence that the chapters underwent some review and revision. In addition, the editors have gone to the trouble to compile author and subject indexes and to write a preface that gives a good overview of the book. These features greatly enhance the text's accessibility and usefulness."—Journal of the American Statistical Association"This collection provides a valuable set of articles on modeling repeated measures data. It is especially interesting in that it presents a great deal of variation in approaches, while stressing the links between these approaches. Thus, it is a more comprehensive treatment of repeated-measure analysis than other collections that focus on only one of these methods....this is an excellent addition to the bookshelf of any researcher who is interested in modeling intraindividual variability."—Contemporary Psychology APA REVIEW OF BOOKS

• Contents: Preface. D.A.Kenny, N. Bolger, D.A. Kashy, Traditional Methods for Estimating Multilevel Models. S.W. Raudenbush, Alternative Covariance Structures for Polynomial Models of Individual Growth and Change. P.J. Curran, A.M. Hussong, Structural Equation Modeling of Repeated Measures Data: Latent Curve Analysis. J.O. Ramsay, Multilevel Modeling of Longitudinal and Functional Data. D. Wallace, S.B. Green, Analysis of Repeated Measures Designs With Linear Mixed Models. J.D. Singer, Fitting Individual Growth Models Using SAS PROC MIXED. T.E. Duncan, S.C. Duncan, F. Li, L.A. Strycker, Multilevel Modeling of Longitudinal and Functional Data. S. Hillmer, Times Series Regressions. J.R. Nesselroade, J.J. McArdle, S.H. Aggen, J.M. Meyers, Dynamic Factor Analysis Models for Representing Process in Multivariate Time-Series.