Bayesian local influence of generalized failure time models with latent variables and multivariate censored data
Publication in refereed journal

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摘要We develop a Bayesian local influence procedure for generalized failure time models with latent variables and multivariate censored data. We propose to use the penalized splines (P-splines) approach to formulate the unknown functions of the proposed models. We assess the effects of minor perturbations to individual observations, the prior distributions of parameters, and the sampling distribution on statistical inference through various perturbation schemes. The first-order local influence measure is used to quantify the degree of minor perturbations to different aspects of a statistical model with the use of Bayes factor as an objective function. Simulation studies show that the empirical performance of the Bayesian local influence procedure is satisfactory. An application to a study of renal disease for type 2 diabetes patients is presented.
著者Ouyang M., Song X. Y.
期刊名稱Journal of Classification
出版年份2020
月份7
卷號37
出版社Springer
頁次298 - 316
國際標準期刊號0176-4268
語言美式英語

上次更新時間 2020-24-11 於 01:48