Longitudinal clinical trials often collect long sequences of binary data monitoring a disease process over time. Our application is a medical study conducted in the US by the Veterans Administration Cooperative Urological ...

This chapter compares two Bayesian nonparametric models that generalize the accelerated failure time model, based on recent work on probability models for predictor-dependent probability distributions. It begins by reviewing ...

This paper deals with asymptotic results on a multivariate ultrastructural errors-in-variables regression model with equation errors Sufficient conditions for attaining consistent estimators for model parameters are presented ...

The early work of Zellner on the multivariate Student-t linear model has been extended to Bayesian inference for linear models with dependent non-normal error terms, particularly through various papers by Osiewalski, Steel ...

Partially linear models are important tools in statistical modelling, combining the flexibility of non–parametric models and the simple interpretation of linear models. Monotonicity constraints appear naturally in certain ...

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for ...

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for ...

Regression models for the mean quality-adjusted survival time are specified from hazard functions of transitions between two states and the mean quality-adjusted survival time may be a complex function of covariates. We ...