Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence
by Judith D. Singer
The art of estimating growth curves: Applied Longitudinal Data Analysis by Singer and Willett
Probably a leading book for data analysts who attempt to develop a longitudinal model or to test hypotheses with respect to changes over time, when both the overall trend is important, but also the individual trend must be considered. This book offers a clear framework to build such models with clear formulae to calculate variance components and goodness of fit measurements. I find myself using this book for both the design stage and the analytical stage of data. The book covers longitudinal models from basic analysis to highly complex cases. It provides access to data and scripts for several statistical programs, that one may use to recode for own use. With some other books complementing this one, the troubles of longitudinal analysis are almost gone. Conceptual diagrams are missing especially for the latent growth curve modeling, but matrix algebra, for whom it is usable, is available, which is the way to understand relationships (covariances) between one time point to another
Dr. Gabriel Liberman – Data-Graph Statistical Consulting
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