Analysis of Survival Data
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.
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Distributions of failure time
Singlesample nonparametric methods
Fully parametric analysis of dependency
Proportional hazards model
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accelerated life model algorithm analysis applications approximate assumed asymptotic binary calculation censoring Chapter component conditional consider constant continuous corresponding covariates defined denote density depend derived discussed effect equation examine example Exercise expectation explanatory variables exponential distribution fail fixed follows further gamma given gives groups hazard function ho(t independent individuals integral interest interpretation interval introduced involving joint limit linear log likelihood logistic matrix maximum likelihood estimator mean measured methods needed normal Note observed obtained parameter particular patients plots possible probability problem procedures properties proportional hazards model random variable ratio regression relative represent require respectively risk set sample Show simple single specified standard statistic Suppose survival survivor function Table theory time-dependent transplant treatment types of failure usually values variance vector Weibull