Applied Logistic Regression / Edition 1by David W. Hosmer Jr., Stanley Lemeshow
Pub. Date: 01/28/1989
In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world exampleswith extensive data sets available over the Internet.
- Publication date:
- Wiley Series in Probability and Statistics - Applied Probability and Statistics Section Series, #237
- Edition description:
- Older Edition
- Product dimensions:
- 6.33(w) x 9.31(h) x 0.99(d)
Table of ContentsIntroduction to the Logistic Regression Model.
The Multiple Logistic Regression Model.
Interpretation of the Coefficients of the Logistic Regression Model.
Model-Building Strategies and Methods for Logistic Regression.
Assessing the Fit of the Model.
Application of Logistic Regression with Different Sampling Models.
Logistic Regression for Matched Case-Control Studies.
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