There is increasing interest in understanding the role of neighborhood-level factors on the health of individuals. Many large-scale epidemiological studies that accurately measure health status of individuals and individual risk factors exist. Sometimes these studies are linked to area-level...

Classical methods for fitting a varying intercept logistic regression model to stratified data are based on the conditional likelihood principle to eliminate the stratum-specific nuisance parameters. When the outcome variable has multiple ordered categories, a natural choice for the outcome...

In this dissertation we investigate bootstrap and likelihood based methods for constructing confidence intervals in some non-standard problems. The non-standard problems studied include problems with non root-n convergence (e.g., cube-root convergence), estimation problems where the parameter is...

The main goal of this thesis is to use concepts and tools from extreme value theory (EVT) to model, make inference and develop prediction tools for the extremes of dependent data with a focus on the financial risk management applications. In the first part of the thesis, a new estimator of the...

Understanding the characteristics of traffic flows is crucial for allocating the necessary resources (bandwidth) to accommodate usersdemand. In this dissertation research, the problem of nonparametric and Moment-Based estimations of network flow characteristics basedon sampled flow data from...

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...

Government policies increasingly promote ethanol and other biofuels for security, air quality, and climate benefits. One chapter of this dissertation develops a model that links the distribution of preferences for ethanol to aggregate price responses and then estimates the model using data from...

Most national health surveys do not permit precise measurement of the health of racial/ethnic subgroups that comprise 1 per cent of the U.S. population. We identify three potentially promising sample design strategies for increasing the accuracy of national health estimates for a small target...

We consider the situation of two ordered categorical variables and a binary outcome variable, where one or both of the categorical variables may have missing values. The goal is to estimate the probability of response of the outcome variable for each cell of the contingency table of categorical...

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...