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Titre: Statistical Methods for Survival Data Analysis (Wiley Series in Probability and Statistics)
�diteur: Wiley-Interscience
Date de parution: 1992
Langue: anglais
ISBN � 10 chiffres: 0471615927
ISBN � 13 chiffres: 9780471615927
Reliure: Couverture rigide
�dition: 2�me �dition
�tat de l'article: Good

A propos de ce titre

Synopsis

Explores the applications of survival data analysis in such fields as criminology, sociology, toxicology, marketing and health insurance practice. This edition has been updated to include material on industrial reliability, life testing and epidemiological applications.

Quatri�me de couverture

The Third Edition of the leading reference on survival data analysis

The study of survival data attempts to predict the probability of response, survival, or mean lifetime; compare; the survival distributions of experimental animals or of human patients; and identify risk and/or prognosis factors. Statistical Methods for Survival Data Analysis, Third Edition examines the statistical methods for analyzing survival data from laboratory studies of animals, clinical and epidemiological studies of humans, and other appropriate applications.

Emphasizing applications over rigorous mathematics, this extremely useful reference provides thorough discussions of the most commonly used parametric and nonparametric methods in survival analysis, as well as guidelines for the planning and design of clinical trials. The authors give special consideration to the study of survival data in biomedical sciences, though the methods are suitable for applications in industrial reliability, the social sciences, and business.

This Third Edition brings this standard in the field up to date with new material and revised references including:

A new introduction to left and interval censored data
The generalized gamma and log–logistic distribution
Estimation procedures for left and interval censored data
Parametric models with covariates
Cox’s proportional hazards model including stratification and time–dependent covariates, and some non–proportional hazards models
Goodness–of–Fit tests and model selection methods
Multiple responses to the logistic regression model
Numerous real–life examples which illustrate key concepts
Computer programming codes in SAS, BMDP, and SPSS for most examples
Related FTP site providing large data sets

These additions and revisions make Statistical Methods for Survival Data Analysis, Third Edition, more valuable than ever as an essential reference for biomedical investigators, statisticians, epidemiologists, and researchers in other disciplines involved or interested in the analysis of survival data.

Les informations fournies dans la section � A propos du livre � peuvent faire r�f�rence � une autre �dition de ce titre.

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