Applied Logistic Regression Author: Rodney X. Sturdivant | Language: English | ISBN:
0470582472 | Format: PDF
Applied Logistic Regression Description
A new edition of the definitive guide to logistic regression modeling for health science and other applicationsThis 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.
- Series: Wiley Series in Probability and Statistics (Book 398)
- Hardcover: 528 pages
- Publisher: Wiley; 3 edition (April 1, 2013)
- Language: English
- ISBN-10: 0470582472
- ISBN-13: 978-0470582473
- Product Dimensions: 8.9 x 6 x 0.8 inches
- Shipping Weight: 1.8 pounds (View shipping rates and policies)
This is an update of the classic text. Excellent reference for the basics of logistic regression. Should be on the bookshelf of anybody who uses the technique regularly.
By Amazon Customer
This book has everything you need to develop a logistic regression model. From a mathematician's point of view, I found the derivation insightful and helped bring a fuller understanding to the methods.
By Jon
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