Applied logistic regression
Author(s)
Bibliographic Information
Applied logistic regression
(Wiley series in probability and mathematical statistics, . Texts and references section)(A Wiley-Interscience publication)
Wiley, c2000
2nd ed
Available at 6 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
-
Library, Institute of Developing Economies, Japan External Trade Organization図
G||330.11||A314795181
Note
Includes bibliographical references (p. 352-365) and index
Description and Table of Contents
Description
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.
Table of Contents
- Introduction to the Logistic Regression Model
- Multiple Logistic Regression
- Interpretation of the Fitted 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
- Special Topics
- References
- Index.
by "Nielsen BookData"