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Applied Survival Analysis : Regression Modeling of Time to Event Data

Applied Survival Analysis : Regression Modeling of Time to Event Data - 99 edition

ISBN13: 978-0471154105

Cover of Applied Survival Analysis : Regression Modeling of Time to Event Data 99 (ISBN 978-0471154105)
ISBN13: 978-0471154105
ISBN10: 0471154105
Cover type:
Edition/Copyright: 99
Publisher: John Wiley & Sons, Inc.
Published: 1999
International: No

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Applied Survival Analysis : Regression Modeling of Time to Event Data - 99 edition

ISBN13: 978-0471154105

David W. Hosmer and Stanley Lemeshow

ISBN13: 978-0471154105
ISBN10: 0471154105
Cover type:
Edition/Copyright: 99
Publisher: John Wiley & Sons, Inc.

Published: 1999
International: No
Summary

Recent years have seen a major growth in the development of methods for analyzing survival time data. At the same time, there has been little in the statistical literature to guide researchers in health-related areas who study time-to-event data. Applied Survival Analysis fills this gap, providing a comprehensive, self-contained introduction to regression modeling used in the analysis of time-to-event data in epidemiological, biostatistical, and other health-related research.

A Practical, Up-To-Date Guide To Modern Methods In The Analysis Of Time To Event Data.

The rapid proliferation of powerful and affordable statistical software packages over the past decade has inspired the development of an array of valuable new methods for analyzing survival time data. Yet there continues to be a paucity of statistical modeling guides geared to the concerns of health-related researchers who study time to event data. This book helps bridge this important gap in the literature.

Applied Survival Analysis is a comprehensive introduction to regression modeling for time to event data used in epidemiological, biostatistical, and other health-related research. Unlike other texts on the subject, it focuses almost exclusively on practical applications rather than mathematical theory and offers clear, accessible presentations of modern modeling techniques supplemented with real-world examples and case studies. While the authors emphasize the proportional hazards model, descriptive methods and parametric models are also considered in some detail.

Key topics covered in depth include:

* Variable selection.
* Identification of the scale of continuous covariates.
* The role of interactions in the model.
* Interpretation of a fitted model.
* Assessment of fit and model assumptions.
* Regression diagnostics.
* Recurrent event models, frailty models, and additive models.
* Commercially available statistical software and getting the most out of it.

Applied Survival Analysis is an ideal introduction for graduate students in biostatistics and epidemiology, as well as researchers in health-related fields.

Author Bio

Hosmer, David W. : University of Massachusetts

DAVID W. HOSMER, Jr., PhD, is a professor of biostatistics in the Department of Biostatistics and Epidemiology of the University of Massachusetts School of Public Health and Health Sciences in Amherst, Massachusetts.


Lemeshow, Stanley : University of Massachusetts

Stanley Lemeshow, PhD, is a professor of biostatistics in the Department of Biostatistics and Epidemiology of the University of Massachusetts School of Public Health and Health Sciences in Amherst, Massachusetts.

Table of Contents

Introduction to Regression Modeling of Survival Data.

Descriptive Methods for Survival Data.

Regression Models for Survival Data.

Interpretation of a Fitted Proportional Hazards Regression Model.

Model Development.

Assessment of Model Adequacy.

Extensions of the Proportional Hazards Model.

Parametric Regression Models.

Other Models and Topics.


Appendices.
References.
Index.

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