Logistic Regression: A Self-Learning Text (Statistics in the Health Sciences)

Kleinbaum, DG

ISBN 10: 0387941428 / ISBN 13: 9780387941424

Published by Springer, 1994

About this Item

This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In poor condition, suitable as a reading copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780387941424.

Seller Inventory # 9772327

Bibliographic Details

• Title: Logistic Regression: A Self-Learning Text (Statistics in the Health Sciences)
• Publisher: Springer
• Publication Date: 1994
• Language: French
• ISBN 10: 0387941428
• ISBN 13: 9780387941424
• Binding: Hardcover
• Condition: Poor
• Weight: 900 grams
• Seller catalogs:
  • Science & Technology

About this title

Synopsis

Emory University, Atlanta, Georgia. Statistics in the Health Sciences Series. Programmed text on this particular mathematical model for students in epidemiology, or for practitioners unfamiliar with statistical methods.

From the Back Cover

This very popular textbook is now in its third edition. Whether students or working professionals, readers appreciate its unique "lecture book" format. They often say the book reads like they are listening to an outstanding lecturer. This edition includes three new chapters, an updated computer appendix, and an expanded section about modeling guidelines that consider causal diagrams.

Like previous editions, this textbook provides a highly readable description of fundamental and more advanced concepts and methods of logistic regression. It is suitable for researchers and statisticians in medical and other life sciences as well as academicians teaching second-level regression methods courses.

The new chapters are:

· Additional Modeling Strategy Issues, including strategy with several exposures, screening variables, collinearity, influential observations and multiple-testing

· Assessing Goodness to Fit for Logistic Regression

· Assessing Discriminatory Performance of a Binary Logistic Model: ROC Curves

The Computer Appendix provides step-by-step instructions for using STATA (version 10.0), SAS (version 9.2), and SPSS (version 16) for procedures described in the main text.

David Kleinbaum is Professor of Epidemiology at Emory University Rollins School of Public Health in Atlanta, Georgia. Dr. Kleinbaum is internationally known for his innovative textbooks and teaching on epidemiological methods, multiple linear regression, logistic regression, and survival analysis. He has taught more than 200 courses worldwide. The recipient of numerous teaching awards, he received the first Association of Schools of Public Health Pfizer Award for Distinguished Career Teaching in 2005.

Mitchel Klein is Research Assistant Professor with a joint appointment in the Environmental and Occupational Health Department and the Epidemiology Department at Emory University Rollins School of Public Health. He has successfully designed and taught epidemiologic methods physicians at Emory’s Master of Science in Clinical Research Program. Dr. Klein is co-author with Dr. Kleinbaum of the second edition of Survival Analysis-A Self-Learning Text.