Analysis of Survival Data
Published on 19. February 2018
212 pages
978-1-351-46660-8 (ISBN)
Description
This monograph contains many ideas on the analysis of survival data to present a comprehensive account of the field. The value of survival analysis is not confined to medical statistics, where the benefit of the analysis of data on such factors as life expectancy and duration of periods of freedom from symptoms of a disease as related to a treatment applied individual histories and so on, is obvious. The techniques also find important applications in industrial life testing and a range of subjects from physics to econometrics. In the eleven chapters of the book the methods and applications of are discussed and illustrated by examples.
Reviews / Votes
"One of those books that any applied statistician who encounters problems involving the analysis of survival data - whether medical statistics or industrial life-testing - will want to have. It is very well written by two eminently qualified individuals. The book has been kept quite short by eliminating many of the mathematical details and proofs..I n summary, this is a good book."-Choice
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Product notice
Reflowable
File size
4,93 MB
ISBN-13
978-1-351-46660-8 (9781351466608)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
D.R. Cox
Analysis of Survival Data
Book
06/1984
1st Edition
Chapman & Hall/CRC
€246.50
Shipment within 10-20 days
Person
Cox, D.R.
Content
Preface, 1 The scope of survival analysis, 2 Distributions of failure time, 3 Parametric statistical analysis: single sample, 4 Single-sample nonparametric methods, 5 Dependence on explanatory variables: model formulation, 6 Fully parametric analysis of dependency, 7 Proportional hazards model, 8 Time-dependent covariates, 9 Several types of failure, 10 Bivariate survivor functions, 11 Self-consistency and the EM algorithm, References, Author index, Subject index
