We propose Bayesian case influence diagnostics for complex survival models. We develop
case deletion influence diagnostics for both the joint and marginal posterior distributions …

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 …

This article develops a variety of influence measures for carrying out perturbation (or
sensitivity) analysis to joint models of longitudinal and survival data (JMLS) in Bayesian …

Case-influence diagnostics are in wide use in classical linear regression and are common in
Bayesian analysis. Most common Bayesian diagnostics assess influence on all parameters; …

As is the case of many studies, the data collected are limited and an exact value is recorded
only if it falls within an interval range. Hence, the responses can be either left, interval or …

In this article, we propose a new approach to the problem of dynamic prediction of survival
data in the presence of competing risks as an extension of the landmark model for ordinary …

The causal effects of Apolipoprotein E allele (APOE) on late-onset Alzheimer's disease (AD)
and death are complicated to define because AD may occur under one intervention but not …

Survival analysis is concerned with nding models to predict the survival of patients or to
assess the e cacy of a clinical treatment. A key part of the model-building process is the …

Graphical methods for model diagnostics are an essential part of the model fitting procedure.
However, in survival analysis, the plotting is always hampered by the presence of censoring …

Joint models for longitudinal and survival data are often used to investigate the association
between longitudinal data and survival data in many studies. A common assumption for joint …