The Statistical Analysis of Failure Time DataWiley, 9 sep. 2002 - 462 sidor * 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. |
Innehåll
Failure Time Models | 31 |
Inference in Parametric Models and Related Topics | 52 |
Relative Risk Cox Regression Models | 95 |
Upphovsrätt | |
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The Statistical Analysis of Failure Time Data John D. Kalbfleisch,Ross L. Prentice Fragmentarisk förhandsgranskning - 2002 |
Vanliga ord och fraser
accelerated failure Amer analysis apply approximate arise assumption asymptotic distribution asymptotic results baseline Biometrics Biometrika bivariate case-cohort case-control censored data censorship Chapter clinical trials cohort competing risks condition consider corresponding counting process Cox model cumulative hazard Data Set defined denotes density depend Dirichlet process discrete discussed efficiency example exponential failure rate failure time data failure time model failure types Fo(t gamma gamma distribution gamma process given hazard function independent censoring Kalbfleisch Kaplan-Meier estimator leukemia likelihood function linear log-rank test marginal marginal likelihood martingale matrix maximum likelihood estimate methods Nonparametric estimation observed obtained partial likelihood Prentice probability procedure proportional hazards model random rank tests regression model regression parameter relative risk relative risk model risk model sample score statistic Section specified study subjects Suppose survival survivor function survivor function estimators t₁ Table time-dependent covariates tion transplant treatment uncensored values variables variance estimator Weibull Wilcoxon Z₁ zero