New sophisticated data analytic strategies have become available to longitudinal researchers, but while information regarding the theory of these methods is available, that theory often does not help the user implement the strategy. Applied Computational Statistics in Longitudinal Research is designed to assist the user to actually run and interpret the results of many of these analytic strategies. Each chapter in the book deals with a different technique and the discussion begins with a summary of the procedure. An example including both the setup of the program and an annotated output are carefully explained. Unlike many other books on these topics, this book helps the user to quickly and easily apply the material to the computer. It can either be used as a companion to the two-volume Statistical Methods in Longitudinal Research (edited by von Eye, Academic Press, September, 1990) or alone to illustrate the applications of statistical methods that can be used in psychology, sociology, medicine, education, and engineering.

Key Features
* Four groups of techniques are discussed:
* General techniques in data analysis
* Methods for structuring change
* Time series modes
* Techniques for analyzing categorical data
Examples of these techniques are presented in a four-step manner:
* General summary of each method
* An outline of computational procedures, including a brief description of the software used
* An annotated example is presented, including the selected data set, its input method, the program for generating the solution, and a portion of the output
* A discussion of results

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