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Logistic Regression is designed for readers whhave a background in statistics at least up tmultiple linear regression, whwant tanalyze dichotomous, nominal, and ordinal dependent variables cross-sectionally and longitudinally The book begins by showing how logistic regression combines aspects of multiple linear regression and loglinear analysis tovercome problems both techniques have with the analysis of dichotomous dependent variables with continuous predictors The logistic regression model is then examined in detail, including how tevaluate the overall model and how tevaluate the impact of the different predictors in the model for different types of research questions Unique tthis book is the extensive consideration qualitative (prediction tables) as well as quantitative indices of how well the model predicts the dependent variable The book then examines what can gwrong with the model and how tdetect and correct it; the use of logistic regression in path analysis; nominal and ordinal dependent variables; modifications tthe logistic regression model when the cases are not completely independent of one another; the use of logistic regression models for longitudinal data with few and with many repeated measurements; and alternatives tlogistic regression In each chapter, the basic model is explained and illustrated with applied examples, with a focus on translating from the research problem tthe implementation of the model, then interpreting the results back tEnglish While not dependent on any one software package, limitations texisting software packages, and ways of getting around those limitations, are examined The book brings together material on logistic regression that is often covered in passing or in limited detail in treatments of other topics such as event history analysis or multilevel analysis, and includes material not elsewhere available on the use of logistic regression with path analysis, linear panel models, and multilevel change models Mathematical notation is kept ta minimum, allowing readers with more limited backgrounds in statistics tfollow the presentation, but the book includes advanced topics that will be of interest tmore statistically sophisticated readers as well
