In this book the most important techniques available for longitudinal data analysis are discussed. This discussion includes simple techniques such as the paired t-test and summary statistics, and also more sophisticated techniques such as generalised estimating equations and random coefficient analysis. A distinction is made between longitudinal analysis with continuous, dichotomous, and categorical outcome variables. The emphasis of the discussion lies in the interpretation of the results of different techniques. Furthermore, special chapters deal with the analysis of two measurements, experimental studies and the problem of missing data in longitudinal studies. Finally, an extensive overview of (and a comparison between) different software packages is provided. This practical guide is suitable for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies. (Author/publisher)
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