The Statistical Analysis of Failure Time Data* Contains additional discussion and examples on left truncation as well as material on more general censoring and truncation patterns. * Introduces the martingale and counting process formulation swil lbe in a new chapter. * Develops multivariate failure time data in a separate chapter and extends the material on Markov and semi Markov formulations. * Presents new examples and applications of data analysis. |
Contents
Failure Time Models | 31 |
Inference in Parametric Models and Related Topics | 52 |
Relative Risk Cox Regression Models | 95 |
Copyright | |
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Other editions - View all
The Statistical Analysis of Failure Time Data John D. Kalbfleisch,Ross L. Prentice Limited preview - 2002 |
The Statistical Analysis of Failure Time Data John D. Kalbfleisch,Ross L. Prentice Limited preview - 2011 |
The Statistical Analysis of Failure Time Data John D. Kalbfleisch,Ross L. Prentice Snippet view - 2002 |
Common terms and phrases
allow analysis apply approach approximate arise associated assumed assumption asymptotic censored data censoring Chapter compared competing condition consider consistent continuous corresponding counting covariates Cox model cumulative defined denotes density depend derived developed discrete discussed disease distribution effect efficiency error estimator event example expectation exponential factor failure fixed follows given gives hazard function independent indicator individual integral intensity interval leukemia log-rank marginal martingale matrix maximum mean measure methods nonparametric normal Note observed obtained occur pairs parameter partial likelihood patients possible Prentice prior probability problem procedure random recurrent regression regression model relative risk respect sample score Show significance simple specified standard Statist Suppose survivor function t₁ Table theory time-dependent tion treatment trial values variables variance variation vector weighted zero