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Logistic Regression: A Primer, Second Edition

Comment from the Stata technical group

This book provides an excellent introduction to logistic regression from first principles. It is an ideal tutorial for those who are familiar with standard linear regression and wish to branch out for the first time into more complex generalized linear models, for which logistic regression (regression with a binary response) is a good starting point. Making the jump from linear regression to logistic regression introduces many issues, including model fitting (least squares versus maximum likelihood), interpretability (odds ratios), interpretation of marginal effects (which are not constant for logistic regression), and regression diagnostics. These topics are covered fully in the context of logistic regression. Where appropriate, the comparison between linear and logistic regression is made. This discussion is also extended to ordinal logistic, multinomial logistic, and probit models. The book's companion website includes data and commands in Stata, SPSS, and R that allow you to reproduce all examples worked in the book.

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