One of the most frequently used regression models for survival data was proposed by Sir David Cox in 1972, the proportional hazards (PH) model. Even though numerous goodness-of-fit tests have been proposed for the PH model, model assumptions are checked infrequently by researchers utilizing it...

A one factor experimental design is developed based on the potential observable outcome framework, sampling from finite population of units and random allocation of treatments. No assumptions are made about the distribution of units and distribution of treatments. We introduce sampling and...

A commonly used method for confounder selection is to determine the percent difference between the crude and adjusted odds ratio of the covariate of interest, and to include the adjusting variable if the difference is greater than 10-15%. However, in logistic regression the crude and adjusted...

The random field model has been applied to model spatial heterogeneity for spatial data in many applications. The purpose of this dissertation is to explore statistical properties of noisy spatial data through estimation of the Gaussian random field. Large sample properties of the Maximum...

In public health studies, it is common for exposure status to be misclassified. In this dissertation, statistical models to adjust for misclassification will be proposed to address four related questions of interest.The first question focuses on exploring the association between a disease and...

In many maintenance treatment trials, patients are first enrolled into an open treatmentbefore they are randomized into treatment groups. During this period, patients are followedover time with their responses measured longitudinally. This design is very common intoday's public health studies of...

The Generalized Additive model (GAM) has been used as a standard tool for epidemiologic analysis exploring the effect of air pollution on population health during the last decade as it allows nonparametric relationships between the independent predictors and response. One major concern to the...

One of the most popular uses for tree-based methods is in survival analysis for censored time data where the goal is to identify factors that are predictive of survival. Tree-based methods, due to their ability to identify subgroups in a hierarchical manner, can sometimes provide a useful...

This paper is concerned with nonparametric methods for comparing medians of paired data with unpaired values on both responses. A new nonparametric test statistic is proposed in this paper based on a Mann-Whitney U test making comparisons across complete and incomplete pairs. A method of finding...

Tree-structured survival analysis (TSSA) is used to recursively detect covariate values that best divide the sample into subsequent subsets with respect to a time to event outcome. The result is a set of empirical classification groups, each of which identifies individuals with more homogeneous...