Applied Logistic Regression

Front Cover
John Wiley & Sons, Apr 1, 2013 - Mathematics - 528 pages
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:

  • A chapter on the analysis of correlated outcome data
  • A wealth of additional material for topics ranging from Bayesian methods to assessing model fit
  • Rich data sets from real-world studies that demonstrate each method under discussion
  • Detailed examples and interpretation of the presented results as well as exercises throughout

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.

 

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LibraryThing Review

User Review  - bluetyson - LibraryThing

A good book that certainly has practical application. It details the rise in use of this particular technique, and where it is applicable. Also details multiple varieties including multinomial and others. This is definitely a mathematics text that is worth the time to take a look at. Read full review

Contents

Logistic Regression Models for the Analysis of Correlated Data
9
The Multiple Logistic Regression Model
35
Interpretation of the Fitted Logistic Regression Model
49
ModelBuilding Strategies and Methods for Logistic Regression
89
Assessing the Fit of the Model
153
5
175
Application of Logistic Regression with Different Sampling
227
Logistic Regression for Matched CaseControl Studies
243
9
351
243
355
Exercises 456
368
Exercises
375
References
395
Index
419
269
431
377
475

Logistic Regression Models for Multinomial and Ordinal
269
6
313

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About the author (2013)

DAVID W. HOSMER, Jr., PhD, is Professor Emeritus of Biostatistics at the School of Public Health and Health Sciences at the University of Massachusetts Amherst.

STANLEY LEMESHOW, PhD, is Professor of Biostatistics and Founding Dean of the College of Public Health at The Ohio State University, Columbus, Ohio.

RODNEY X. STURDIVANT, PhD, is Associate Professor and Founding Director of the Center for Data Analysis and Statistics at the United States Military Academy at West Point, New York.