Testing for the ratio of binomial proportions (often called the relative risk) is quite common in clinical trials and epidemiology study or more generally in the pharmaceutical setting. Although this is an easy problem when we have large sample sizes, it becomes more challenging when sample...

Over the past few decades correspondence analysis has gained an international reputation as a powerful statistical tool for the graphical analysis of contingency tables. This popularity stems from its development and application in many European countries, especially France, and its use has...

Log-linear modeling is a popular statistical tool for analysing a contingency table. This presentation focuses on an alternative approach to modeling ordinal categorical data. The technique, based on orthogonal polynomials, provides a much simpler method of model fitting than the conventional...

We define and investigate classes of statistical models for the analysis of associations between variables, some of which are qualitative and some quantitative. In the cases where only one kind of variables is present, the models are well-known models for either contingency tables or covariance...

Item Response Theory (IRT) models are the basis of modern educational measurement. In order to increase testing efficiency, modern tests make ample use of groups of questions associated with a single stimulus (testlets). This violates the IRT assumption of local independence. However, a set of...

The point source is the most common type of source to be modeled for its effect on air pollution. Point sources provide auxiliary information that may impact both the mean and covariance structure of measured responses, but these possible impacts are often overlooked by spatial modelers. In this...

In this paper, I develop and estimate a dynamic model of strategicnetwork formation with heterogeneous agents. The main theoretical resultis the existence of a unique stationary equilibrium, which characterizesthe probability of observing a specific network in the data. As aconsequence, the...

Univariate hierarchical Bayes models are being vigorously researched for use in disease mapping, engineering, geology, and ecology. This dissertation shows how the models can also be used to build modelbased risk maps for areabased roadway traffic crashes. Countylevel vehicle crash records and...

A large body of literature studies the issues of the option price and other ex-antewelfare measures under the microeconomic theory to valuate reductions of risks inherentin environment and human health. However, it does not offer a careful discussion of howto estimate risk reduction values using...

This thesis develops a new Bayesian approach to structural break modeling. The focuses of the approach are the modeling of in-sample structural breaks and forecasting time series allowing out-of-sample breaks. Our model has some desirable features. First, the number of regimes is not fixed and...