Lifetime Data Anal - Bayesian local influence for survival models.

Tópicos

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Resumo

The aim of this paper is to develop a Bayesian local influence method (Zhu et al. 2009, submitted) for assessing minor perturbations to the prior, the sampling distribution, and individual observations in survival analysis. We introduce a perturbation model to characterize simultaneous (or individual) perturbations to the data, the prior distribution, and the sampling distribution. We construct a Bayesian perturbation manifold to the perturbation model and calculate its associated geometric quantities including the metric tensor to characterize the intrinsic structure of the perturbation model (or perturbation scheme). We develop local influence measures based on several objective functions to quantify the degree of various perturbations to statistical models. We carry out several simulation studies and analyze two real data sets to illustrate our Bayesian local influence method in detecting influential observations, and for characterizing the sensitivity to the prior distribution and hazard function.

Resumo Limpo

aim paper develop bayesian local influenc method zhu et al submit assess minor perturb prior sampl distribut individu observ surviv analysi introduc perturb model character simultan individu perturb data prior distribut sampl distribut construct bayesian perturb manifold perturb model calcul associ geometr quantiti includ metric tensor character intrins structur perturb model perturb scheme develop local influenc measur base sever object function quantifi degre various perturb statist model carri sever simul studi analyz two real data set illustr bayesian local influenc method detect influenti observ character sensit prior distribut hazard function

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