This book discusses the most important techniques available for longitudinal data analysis‎,‎ from simple techniques such as the paired t‎-test and summary statistics‎,‎ to more sophisticated ones such as generalized estimating of equations and mixed model analysis‎.‎ A distinction is made between longitudinal analysis with continuous‎,‎ dichotomous and categorical outcome variables‎.‎ The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques‎.‎ The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis‎.‎ Explanations have been clarified where necessary and several chapters have been completely rewritten‎.‎ The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed‎.‎ Finally‎,‎ an extensive overview and comparison of different software packages is provided‎.‎ This practical guide is essential for non‎-statisticians and researchers working with longitudinal data from epidemiological and clinical studies‎.‎