Modelling Survival Data in Medical ResearchModelling Survival Data in Medical Research describes the modelling approach to the analysis of survival data using a wide range of examples from biomedical research.Well known for its nontechnical style, this third edition contains new chapters on frailty models and their applications, competing risks, non-proportional hazards, and dependent censo |
Contents
Survival analysis | 1 |
Some nonparametric procedures | 17 |
The Cox regression model | 57 |
Model checking in the Cox regression model | 131 |
Parametric proportional hazards models | 171 |
Accelerated failure time and other parametric models | 221 |
Model checking in parametric models | 275 |
Timedependent variables | 295 |
Nonproportional hazards and institutional comparisons | 381 |
Competing risks | 405 |
Multiple events and event history modelling | 429 |
Dependent censoring | 457 |
Sample size requirements for a survival study | 471 |
Maximum likelihood estimation | 487 |
Additional data sets | 491 |
Bibliography | 499 |
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Common terms and phrases
accelerated failure age group baseline hazard function baseline survivor function cause-specific censored survival Chapter coefficients competing risks confidence interval corresponding counting process Cox regression model Cox-Snell residuals cumulative hazard function cumulative incidence function data set dependent censoring estimated survivor function event Example explanatory variables exponential distribution factor failure time model fitted model frailty effects gamma hazard of death hazard ratio hi(t ho(t included indicator variables interval-censored ith individual Kaplan-Meier estimate likelihood function linear log Î log-cumulative hazard plot log-logistic lognormal martingale residuals maximised median survival methods model that contains nephrectomy null hypothesis number of deaths obtained P-value parameter estimates parametric models patients positively stained probability proportional hazards model random effects random variable recurrence result risk score So(t standard error survival analysis survival data Table time-dependent variables transplant treatment effect treatment group tumour unity values variance vector Weibull distribution Weibull model zero