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Applied Logistic Regression
A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression , Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include: Applied Logistic Regression , Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines.
528 pages, Hardcover
First published July 1, 1989
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Displaying 1 - 3 of 3 reviews
July 12, 2010
Logistic regression is a very handy statistical tool. It does not demand much of the data (no need for variables to be normally distributed). Also, it can be used with dichotomous dependent variables. Multiple regression is often used for such purposes, but--technically--that might provide misleading results. This is one of the classic books outlining the use (and abuse) of logistic regression analysis.
April 23, 2021
This book is awesome to self-learn in-depth about logistic regression. The author designed the book nicely with step by step explanation of real-world data.
Displaying 1 - 3 of 3 reviews