Analysis of Survival DataThis 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. |
Contents
Distributions of failure time | 13 |
single sample | 32 |
Singlesample nonparametric methods | 48 |
model formulation | 62 |
Fully parametric analysis of dependency | 80 |
Proportional hazards model | 91 |
CONTENTS vii | 107 |
Several types of failure | 142 |
Bivariate survivor functions | 156 |
Selfconsistency and the EM algorithm | 165 |
References | 183 |
| 198 | |
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absence of censoring accelerated life model algorithm analysis approximate asymptotic baseline Bibliographic notes binary c₁ censored data censored individuals Chapter chi-squared distribution competing risk component consider corresponding d₁ defined denote density depend discussed EM algorithm equation example explanatory variables exponential distribution exponential family F₁(t Fo(t FURTHER RESULTS gamma distribution given groups h₁ h₁(t hazard function ho(t independent interval joint distribution keRi likelihood function log likelihood log logistic log normal log rank test maximum likelihood estimator methods null hypothesis number of failures observed failure obtained parameter partial likelihood patients possible procedures product-limit estimator proportional hazards model random variable regression RESULTS AND EXERCISES risk set sample second derivatives Section Show statistic Suppose survival distribution survivor function T₁ theory time-dependent covariates transplant types of failure uncensored v₁ values variance vector Weibull distribution x₁ z₁ z₁(t β₁
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