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Some of the material in is restricted to members of the community. By logging in, you may be able to gain additional access to certain collections or items. If you have questions about access or logging in, please use the form on the Contact Page.
Statisticians often encounter data in the form of a combination of discrete and continuous outcomes. A special case is zero-inflated longitudinal data where the response variable has a large portion of zeros. These data exhibit...
Recurrent events data are rising in all areas of biomedical research. We present a model for recurrent events data with the same link for the intensity and mean functions. Simple interpretations of the covariate effects on both the...
It is often assumed that all uncensored subjects will eventually experience the event of interest in standard survival models. However, in some situations when the event considered is not death, it will never occur for a proportion of...
Polychotomous quantal response models are widely used in medical and econometric studies to analyze categorical or ordinal data. In this study, we apply the Bayesian methodology through a mixed-effects polychotomous quantal response...
Image analysis often requires dimension reduction before statistical analysis, in order to apply sophisticated procedures. Motivated by eventual applications, a variety of criteria have been proposed: reconstruction error, class...
The El Niรฑo Southern Oscillation (ENSO) is an important natural climate variation that affects large portions of the world. The changing magnitude and frequency of ENSO reveals that it is getting stronger as measured by the maximum...
My dissertation presents a novel statistical method to estimate a sparse signal in functional data and to construct confidence bands for the signal. Existing methods for inference for the mean function in this framework include smoothing...
We develop a modeling framework to simultaneously evaluate various types of predictability in stock returns, including stocks' sensitivity ("betas") to systematic risk factors, stocks' abnormal returns unexplained by risk factors (...
A class of hierarchical Bayesian models is introduced for adverse birth outcomes such as preterm birth, which are assumed to follow a conditional binomial distribution. The log-odds of an adverse outcome in a particular county, logit(p(i...
Many characteristics for predicting death due to coronary heart disease are measured on a continuous scale. These characteristics, however, are often categorized for clinical use and to aid in treatment decisions. We would like to derive...
This dissertation presents, applies, and evaluates a statistical approach to an ocean circulation problem. The objective is to produce a map of ocean velocity in the North Atlantic based on sparse measurements along ship tracks, based on...
The Barker Hypothesis states that maternal and `in utero' attributes during pregnancy affects a child's cardiovascular health throughout life. We present an analysis of a unique longitudinal dataset from Jamaica that consists of three...
This research work is an attempt to illustrate the versatility and wide applications of the field of statistical science. Specifically, the research work involves the application of statistics in the field of law. The application will...
In this study, we will examine the Bayesian Dynamic Survival Models, time-varying coefficients models from a Bayesian perspective, and their applications in the aging setting. The specific questions we are interested in are: Do the...
In this thesis we investigate post-model selection properties of L1 penalized weighted least squares estimators in regression models with a large number of variables M and correlated errors. We focus on correct subset selection and on...
In this thesis, based on an orthonormal series expansion, we propose a new nonparametric method to estimate copula density functions. Since the basis coefficients turn out to be expectations, empirical averages are used to estimate these...
One of the desirable properties of the coefficient of determinant (R2 measure) is that its values for different models should be comparable whether the models differ in one or more predictors, or in the dependent variable, or whether the...
Different methods have been proposed to model the J-shaped or U-shaped relationship between a risk factor and mortality so that the optimal risk-factor value (nadir) associated with the lowest mortality can be estimated. The basic model...
Clinicians employ prognostic survival models for diseases such as coronary heart disease and cancer to inform patients about risks, treatments, and clinical decisions (Altman and Royston 2000). These prognostic models are not useful...
This thesis presents a stochastic process and time series study on corporate credit rating and market implied rating transitions. By extending an existing model, this paper incorporates the generalized autoregressive conditional...
This dissertation develops novel single random effect models as well as bivariate correlated random effects model for clustered data with bivariate mixed responses. Logit and identity link functions are used for the binary and continuous...
This dissertation is on analysis of invariants of a 3D configuration from its 2D images in pictures of this configuration, without requiring any restriction on the camera positioning relative to the scene pictured. We briefly review some...
This paper aims at analyzing a macro economy with a continuum of infinitely-lived households that make rational decisions about consumption and wealth savings in the face of employment and aggregate productivity shocks. The heterogeneous...
The generalized linear model and particularly the logistic model are widely used in public health, medicine, and epidemiology. Goodness-of-fit tests for these models are popularly used to describe how well a proposed model fits a set of...
We perform a quasi-3D Bayesian inversion of oceanographic tracer data from the South Atlantic Ocean. Initially we are considering one active neutral density layer with an upper and lower boundary. The available hydrographic data is...
We examine the impact of missing data in two settings, the development of prognostic models and the addition of new risk factors to existing risk functions. Most statistical software presently available perform complete case analysis, ...
In this dissertation we develop probability models for human shapes and apply those probability models to the problems of image segmentation and human identi_cation by gait recognition. To build probability models on human shapes, we...
We study a weighted least squares (WLS) estimator for Aalen's additive risk model which allows for a very flexible handling of covariates. We divide the follow-up period into intervals and assume a constant hazard rate in each interval....
In this dissertation, we examine binary correlated data with present/absent component or missing data that are related to binary responses of interest. Depending on the data structure, correlated binary data can be referred as emph...
In this thesis we investigate statistical modelling of neural activity in the brain. We first develop a framework which is an extension of the state-space Generalized Linear Model (GLM) by Eden and colleagues [20] to include the effects...
For survival outcomes, usually, statistical equivalent tests to show a new treatment therapeutically equivalent to a standard treatment are based on the Cox (1972) proportional hazards assumption. We present an alternative method based...
Risk prediction plays an important role in clinical medicine. It not only helps in educating patients to improve life style and in targeting individuals at high risk, but also guides treatment decisions. So far, various instruments have...
The importance of major risk factors, such as hypertension, total cholesterol, body mass index, diabetes, smoking, for predicting incidence and mortality of Coronary Heart Disease (CHD) is well known. In light of the fact that age is...
This thesis presents a Bayesian approach to Meta-Regression and Individual Patient Data (IPD) Meta-analysis. The focus of the research is on establishing the relationship between Body Mass Index (BMI) and all-cause mortality. This has...
We are interested in differences between risk models based on Coronary Heart Disease (CHD) incidence, or morbidity, compared to risk models based on CHD death. Risk models based on morbidity have been developed based on the Framingham...
The stochastic modeling of financial assets is essential to the valuation of financial products and investment decisions. These models are governed by certain parameters that are estimated through a process known as calibration. Current...
With ever increasing complexity of observational and theoretical data models, the sufficiency of the classical statistical techniques, designed to be applied only on vector quantities, is being challenged. Nonlinear statistical analysis...
We explore the non-Gaussianity of hyperspectral data and present probability models that capture variability of hyperspectral images. In particular, we present a nonparametric probability distribution that models the distribution of the...
The purpose of this study is to explore the mathematical preference of high school AP Calculus students by examining their tendencies for using differing methods of thought. A student's preferred mode of thinking was measured on a scale...
The Cox proportional hazards model is routinely used to determine the time until an event of interest. Two time scales are used in practice: follow up time and chronological age. The former is the most frequently used time scale both in...
A multilevel logistic regression approach provides an attractive and practical alternative for the study of Differential Item Functioning (DIF). It is not only useful for identifying items with DIF but also for explaining the presence of...
This thesis presents the new development of the 3rd generation femtosecond diffractometer (FED) in Professor Jim Cao's group and its application to study ultrafast structural dynamics of solid state materials. The 3rd generation FED...
Some of the material in is restricted to members of the community. By logging in, you may be able to gain additional access to certain collections or items. If you have questions about access or logging in, please use the form on the Contact Page.
