If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, Paul Allison's <i>Logistic Regression Using SAS: Theory and Application, Second Edition</i>, is for you! Informal and nontechnical, this book both explains the theory behind
Applied Logistic Regression, Second Edition
โ Scribed by David W. Hosmer, Stanley Lemeshow(auth.), Walter A. Shewhart, Samuel S. Wilks(eds.)
- Publisher
- John Wiley & Sons, Inc.
- Year
- 2000
- Tongue
- English
- Leaves
- 396
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
From the reviews of the First Edition.
"An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references."
-Choice
"Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent."
-Contemporary Sociology
"An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical."
-The Statistician
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 examples-with extensive data sets available over the Internet.
Content:Chapter 1 Introduction to the Logistic Regression Model (pages 1โ30):
Chapter 2 Multiple Logistic Regression (pages 31โ46):
Chapter 3 Interpretation of the Fitted Logistic Regression Model (pages 47โ90):
Chapter 4 Model?Building Strategies and Methods for Logistic Regression (pages 91โ142):
Chapter 5 Assessing the Fit of the Model (pages 143โ202):
Chapter 6 Application of Logistic Regression with Different Sampling Models (pages 203โ222):
Chapter 7 Logistic Regression for Matched Case?Control Studies (pages 223โ259):
Chapter 8 Special Topics (pages 260โ351):
๐ SIMILAR VOLUMES
<p><b>Praise for the<i> First Edition</i></b></p><p><b>"The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." <i>?The American Statistician</i></b></p><p>Fully revised to reflect the latest me
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 relations
<b>A new edition of the definitive guide to logistic regression modeling </b><b>for health science and other applications</b><p>This thoroughly expanded <i>Third Edition </i>provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by exa
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 relationshi