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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.


Table of contents (16 chapters)

Introduction to Logistic Regression

Kleinbaum, David G. (et al.)

Important Special Cases of the Logistic Model

Kleinbaum, David G. (et al.)

Pages 41-71

Computing the Odds Ratio in Logistic Regression

Kleinbaum, David G. (et al.)

Pages 73-101

Maximum Likelihood Techniques: An Overview

Kleinbaum, David G. (et al.)

Pages 103-127

Statistical Inferences Using Maximum Likelihood Techniques

Kleinbaum, David G. (et al.)

Pages 129-164

Modeling Strategy Guidelines

Kleinbaum, David G. (et al.)

Pages 165-202

Modeling Strategy for Assessing Interaction and Confounding

Kleinbaum, David G. (et al.)

Pages 203-239

Additional Modeling Strategy Issues

Kleinbaum, David G. (et al.)

Pages 241-299

Assessing Goodness of Fit for Logistic Regression

Kleinbaum, David G. (et al.)

Pages 301-343

Assessing Discriminatory Performance of a Binary Logistic Model: ROC Curves

Kleinbaum, David G. (et al.)

Pages 345-387

Analysis of Matched Data Using Logistic Regression

Kleinbaum, David G. (et al.)

Pages 389-428

Polytomous Logistic Regression

Kleinbaum, David G. (et al.)

Pages 429-462

Ordinal Logistic Regression

Kleinbaum, David G. (et al.)

Pages 463-488

Logistic Regression for Correlated Data: GEE

Kleinbaum, David G. (et al.)

Pages 489-538

GEE Examples

Kleinbaum, David G. (et al.)

Pages 539-565

Other Approaches for Analysis of Correlated Data

Kleinbaum, David G. (et al.)
ISBN
978-1-4419-1741-6
EAN
9781441917416
Editor
Springer Verlag Gmbh&Co. Kg
Stock
NO
Idioma
Inglés
Nivel
Profesional
Formato
Encuadernado
Tapa Dura
Páginas
-
Largo
-
Ancho
-
Peso
-
Edición
Fecha de edición
19-06-2018
Año de edición
2018
Nº de ediciones
1
Colección
-
Nº de colección
-