Applied Survival Analysis
Regression Modeling of Time to Event Data
Wiley (Publisher)
1st Edition
Published on 21. January 1999
Book
Hardback
408 pages
978-0-471-15410-5 (ISBN)
Article exhausted; check for reprint
Description
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.
Reviews / Votes
"This is actually a great book to read. It has a wealth of examples and applications." (Technometrics, February, 2001) ...ideal textbook for people with knowledge of regression analysis who want to become acquainted with the methods of survival analysis. (International Journal of Epidemiology, Volume 30 No 2 2001) "...highly recommended..." (Statistical Methods in Medical Research, August 1999)More details
Series
Edition
1., Aufl.
Language
English
Place of publication
New York
United States
Publishing group
John Wiley and Sons Ltd
Target group
College/higher education
Professional and scholarly
Illustrations
Illustrations
Dimensions
Height: 24 cm
Width: 16 cm
Weight
680 gr
ISBN-13
978-0-471-15410-5 (9780471154105)
Schweitzer Classification
Other editions
New editions

David W. Hosmer | Stanley Lemeshow | Susanne May
Applied Survival Analysis
Regression Modeling of Time to Event Data
Book
04/2008
2nd Edition
Wiley
€154.50
Shipment within 10-20 days
Persons
DAVID W. HOSMER, Jr., PhD, and STANLEY LEMESHOW, PhD, are both professors of biostatistics in the Department of Biostatistics and Epidemiology of the University of Massachusetts School of Public Health and Health Sciences in Amherst, Massachusetts.
Content
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.