Applied Logistic Regression

David W Hosmer

ISBN 10: 0471356328 / ISBN 13: 9780471356325

Published by John Wiley and Sons Ltd, 2000

About this Item

Since the late 1960s the logistic regression (LR) model has become the standard method for regression analysis of dichotomous data in many fields, especially in the health sciences. This text offers an introduction to the LR model and examines its use in methods for modelling.

Seller Inventory # CIN0471356328VG

Bibliographic Details

• Title: Applied Logistic Regression
• Publisher: John Wiley and Sons Ltd
• Publication Date: 2000
• Language: English
• ISBN 10: 0471356328
• ISBN 13: 9780471356325
• Binding: Hardback
• Edition: 2nd Edition
• Condition: Very Good

About this title

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.

About the Author

DAVID W. HOSMER, PhD, is Professor of Biostatistics at the School of Public Health and Health Sciences at the University of Massachusetts at Amherst.

STANLEY LEMESHOW, PhD, is Professor of Biostatistics and Director of the Biostatistics Program at The Ohio State University.