A basic estimation strategy in sample surveys is to weight units inversely proportional to the probability of selection and response. Response weights in this method are usually estimated by the inverse of the sample-weighted response rate in an adjustment cell, that is, the ratio of the sum of...

Times between sequentially ordered events (gap times) are often of interest in biomedical studies. For example, in a cancer study, the gap times from incidence-to-remission and remission-to-recurrence may be examined. Such data are usually subject to right censoring, and within-subject failure...

In a common ROC study design, several readers are asked to rate diagnostics of the same cases processed under different modalities. We describe a Bayesian hierarchical model that facilitates the analysis of this study design by explicitly modelling the three sources of variation inherent to it....

In many biomedical studies, it is of interest to assess dependence between bivariate failure time data. We focus here on a special type of such data, referred to as semi-competing risks data. In this article, we develop methods for making inferences regarding dependence of semi-competing risks...

There has been some recent work in the statistical literature for modelling the relationship between tumour biology properties and tumour progression in screening trials. While non-parametric methods have been proposed for estimation of the tumour size distribution at which metastatic transition...

In assessing the mechanism of treatment efficacy in randomized clinical trials, investigators often perform mediation analyses by analyzing if the significant intent-to-treat treatment effect on outcome occurs through or around a third intermediate or mediating variable: indirect and direct...

Mathematical models which relate the growth rate of a microorganism to a single limiting substrate concentration have long been established. In recent years, it has become apparent that, under certain conditions, the growth rate of an organism may be simultaneously limited by two or more...

This dissertation looks at two different problems essentially. In recent years, pseudo observations have found application in multi-state survival models, models for mean lifetime and competing risks to name a few. We have investigated the performance of estimates and confidenceintervals based...

Recently, a Bayesian paradigm was constructed for Phase I trial designs that allows for theevaluation and comparison of several nested treatment schedules, each consisting of a sequence ofadministration times. In contrast to traditional Phase I trial designs that seek to find a maximum...

The hybrid bootstrap uses resampling ideas to extend the duality approach to interval estimation for a parameter of interest when there are nuisance parameters. The confidence region constructed by the hybrid bootstrap may perform much better than the ordinary bootstrap region in situations...