When determining the most appropriate method for analyzing
longitudinal data, you must first consider what research question
you want to answer. In this book, McArdle and Nesselroade identify
five basic purposes of longitudinal structural equation modeling.
For each purpose, they present the most useful strategies and
models. Two important but underused approaches are emphasized:
multiple factorial invariance over time and latent change scores.
The book covers a wealth of models in a straightforward,
understandable manner. Rather than overwhelm the reader with an
extensive amount of algebra, the authors use path diagrams and
emphasize methods that are appropriate for many uses.
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