Bayesian Bootstrap for Proportional Hazards Models
نویسندگان
چکیده
Bayesian bootstrap was proposed by Rubin (1981) and its theoretical properties and application to survival models without covariates was studies by Lo (1993) and others. Bayesian bootstrap, empirical likelihood and bootstrap are diierent approaches based on the same idea, approximating the nonparametric model with the family of distributions whose supports are the set of observations. Based on this observation, we extended the Bayesian bootstrap framework to survival models with covariates and studied its large sample theory. The full Bayesian analysis of the proportional hazards models has been developed by many authors, but practitioners' routine use may be hampered due to the complexity of its computation. Bayesian bootstrap gives an simple alternative.
منابع مشابه
Point Prediction for the Proportional Hazards Family under Progressive Type-II Censoring
In this paper, we discuss dierent predictors of times to failure of units censored in multiple stages in a progressively censored sample from proportional hazard rate models. The maximum likelihood predictors, best unbiased predictors and conditional median predictors are considered. We also consider Bayesian point predictors for the times to failure of units. A numerical example and a Monte C...
متن کاملInference for the Proportional Hazards Family under Progressive Type-II Censoring
In this paper, the well-known proportional hazards model which includes several well-known lifetime distributions such as exponential,Pareto, Lomax, Burr type XII, and so on is considered. With both Bayesian and non-Bayesian approaches , we consider the estimation of parameters of interest based on progressively Type-II right censored samples. The Bayes estimates are obtained based on symmetric...
متن کاملThe evaluation of Cox and Weibull proportional hazards models and their applications to identify factors influencing survival time in acute leukem
Introduction: The most important models used in analysis of survival data is proportional hazards models. Applying this model requires establishment of the relevance proportional hazards assumption, otherwise it world lead to incorrect inference. This study aims to evaluate Cox and Weibull models which are used in identification of effective factors on survival time in acute leukemia. Me...
متن کاملBias Evaluation in Theproportional Hazards Modele
We consider two approaches for bias evaluation and reduction in the proportional hazards model (PHM) proposed by Cox. The rst one is an analytical approach in which we derive the n ?1 bias term of the maximum partial likelihood estimator. The second approach consists of resampling methods, namely the jackknife and the bootstrap. We compare all methods through a comprehensive set of Monte Carlo ...
متن کاملComputer programs to estimate overoptimism in measures of discrimination for predicting the risk of cardiovascular diseases.
BACKGROUND Development of chronic disease risk prediction models has become a growing area of research in recent years. The internal validity of such models is sometimes lower than estimated from the development sample. Overfitting or overoptimism of the developed model and/or differences between the samples are likely causes for this. For modelling of an uncommon outcome, bootstrapping for ove...
متن کامل