Applied Logistic Regression

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.

Get the book

Amazon.com

Search the book

eBay.com

Search the book

Other editions

• 

  Applied Logistic Regression

  • 2013-06-03
  • 392 pages
  • Paperback
  • Wiley-Interscience
• 

  Applied Logistic Regression

  • 2013-04-01
  • 528 pages
  • Paperback
  • John Wiley & Sons
• 

  Applied Logistic Regression

  • 2013-02-26
  • 528 pages
  • Ebook
  • John Wiley & Sons
• 

  Applied Logistic Regression

  • 2004-10-28
  • 392 pages
  • Paperback
  • John Wiley & Sons

Similar books

• 

  Solutions Manual to accompany Applied Logistic Regression

  By Stanley Lemeshow, David W. Hosmer, Jr.

  Presenting information on logistic regression models, this work explains difficult concepts through illustrative examples. This is a solutions manual to accompany applied Logistic Regression, 2nd Edition.

• 

  Applied Logistic Regression Analysis

  By Scott Menard

  The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered.

• 

  Applied Logistic Regression, Second Edition: Book and Solutions Manual Set

  By Stanley Lemeshow, Elizabeth D. Cook, David W. Hosmer

  From the reviews of the First Edition.

• 

  Applied Logistic Regression Analysis

  By Scott Menard

  Emphasizing the parallels between linear and logistic regression, Scott Menard explores logistic regression analysis and demonstrates its usefulness in analyzing dichotomous, polytomous nominal, and polytomous ordinal dependent variables. The book...

• 

  Applied Ordinal Logistic Regression Using Stata: From Single-Level to Multilevel Modeling

  By Xing Liu

  The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata helps readers learn how to conduct analyses, interpret the results from ...

• 

  Applied Survival Analysis: Regression Modeling of Time-to-Event Data

  By Stanley Lemeshow, Susanne May, David W. Hosmer

  Rothman,K.J. and Greenland,S. (1998). Modern Epidemiology.3rd edition. LippincottRaven., Philadelphia, PA. Royston, P(2001). Flexible parametric alternatives to the Coxmodeland more. TheStata Journal, 1(1 ): 1–28. Royston, P.(2004).

• 

  Applied Logistic Regression

  By Stanley Lemeshow, David W. Hosmer

  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 -- ...

• 

  Applied Regression Modeling

  By Iain Pardoe

  The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work. Praise for the First Edition "The attention to detail is impressive.

• 

  Best Practices in Logistic Regression

  By Jason W. Osborne

  'Tis better to use a logit or probit link function than to inappropriately use ordinary least squares regression with binary or categorical dependent variables . . .” —attributed to Warren Shakespeare, William's younger statistician ...

• 

  Logistic Regression: From Introductory to Advanced Concepts and Applications

  By Scott Menard

  Glenview, IL: Scott, Foresman. Lipsey, M. W. (1998). Design sensitivity: Statistical power for applied experimental research. In L. Bickman and D. J. Rog (eds.), Handbook of Applied Social Research Methods. Thousand Oaks, CA: Sage.