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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.
With rapid advances in data acquisition and storage techniques, modern scientific investigations in epidemiology, genomics, imaging and networks are increasingly producing challenging data structures in the form of high-dimensional...
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...
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 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...
We study group variable selection on multivariate regression model. Group variable selection is equivalent to select the non-zero rows of coefficient matrix, since there are multiple response variables and thus if one predictor is...
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...
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...
In this essay we present analysis examining the basic dietary structure and its relationship to mortality in the first National Health and Nutrition Examination Survey (NHANES I) conducted between 1971 and 1975. We used results from 24...
Heart disease and premature birth continue to be the leading cause of mortality and neonatal mortality in large parts of the world. They are also estimated to have the highest medical expenditures in the United States. Early detection of...
Big data has brought both opportunities and challenges to our research community. Complex models can be built with large volumes of data researchers have never had access before. In this study we explore the structure learning of...
We consider change-point detection and estimation in two different settings. The objective is to halt a process when the process generating observations deviates from a specified in control standard, in which case the process is referred...
Estimation of a survival function is a very important topic in survival analysis with contributions from many authors. This dissertation considers estimation of confidence intervals for the survival function based on right censored or...
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...
Frailty has been defined as a state of increased vulnerability to adverse outcomes. The concept of frailty has been centered around counting the number of deficits in health, which can be diseases, disabilities, or symptoms. However, ...
This dissertation questions the dominant paradigm of a 'cultural revolution' in ancient Rome and Italy, as a product of the Augustan age. It also calls into consideration the notions that aristocratic elites were cultural trend-setters...
Prognostic models are widely used in medicine to estimate particular patients' risk of developing disease. For cardiovascular disease risk numerous prognostic models have been developed for predicting cardiovascular disease including...
ROC curves are often used to evaluate predictive accuracy of statistical prediction models. This thesis studies other measures which not only incorporate the statistical but also the clinical consequences of using a particular prediction...
This dissertation presents some topics in spatial statistics and their application in biostatistics and environmental statistics. The field of spatial statistics is an energetic area in statistics. In Chapter 2 and Chapter 3, the goal is...
Blocking methods of thresholding have demonstrated many advantages over term-by-term methods in adaptive wavelet estimation. These blocking methods are resolution-level specific, meaning the coefficients are grouped together only within...
Studies have suggested that diabetes is a stronger risk factor for coronary heart disease (CHD) in women than in men. We present a meta-analysis of person-level data from 42 cohort studies in which diabetes, CHD mortality and potential...
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...
The autoregressive conditional heteroskedasticity (ARCH) and generalized autoregressive conditional heteroskedasticity (GARCH) models take the dependency of the conditional second moments. The idea behind ARCH/GARCH model is quite...
In this study, we propose a robust method holding a selective shrinkage power for small area estimation with automatic random effects selection referred to as SARS. In our proposed model, both fixed effects and random effects are treated...
Due to the importance of seeing profile change in devices such as of medical apparatus, measuring the change point in variability of a different functions is important. In a sequence of functional observations (each of the same length), ...
Nonstationary nonparametric densities occur naturally including applications such as monitoring the amount of toxins in the air and in monitoring internet streaming data. Progress has been made in estimating these densities, but there is...
Variable selection is an important aspect of modeling. Its aim is to distinguish between the authentic variables which are important in predicting outcome, and the noise variables which possess little to no predictive value. In other...
The longitudinal data analysis plays an important role in a lot of applications today. It is defined by many measurements are obtained over many times. These measurements has complicated correlation structure because they are obtained...
As we routinely encounter high-throughput datasets in complex biological and environment research, developing novel models and methods for variable selection has received widespread attention. In this dissertation, we addressed a few key...
In survival analysis, data on the time until a specific criterion event (or "endpoint") occurs are analyzed, often with regard to the effects of various predictors. In the classic applications, the criterion event is in some sense a...
Van Valen's Red Queen hypothesis states that within a homogeneous taxonomic group the age is statistically independent of the rate of extinction. The case of the Red Queen hypothesis being addressed here is when the homogeneous taxonomic...
The age of big data has re-invited much interest in dimension reduction. How to cope with high-dimensional data remains a difficult problem in statistical learning. In this study, we consider the task of dimension reduction---projecting...
In this paper we are interested in predicting death with the underlying cause of coronary heart disease (CHD). There are two prognostic modeling methods used to predict CHD: the logistic model and the proportional hazard model. For this...
Mediation analysis seeks to quantify the portion of the effect of an exposure on an outcome that occurs through a postulated causal pathway. Changes in an observable mediator variable reflect activity on the pathway. To measure effects...
In meta-analysis practice, effect measures from individual studies are synthesized to produce an overall result. Researchers frequently face studies that report the same outcome differently. The first scenario is that continuous outcomes...
Monitoring data arising from a process a practitioner desires to be in-control is a typical task in Statistical Process Control (SPC). These data are generated sequentially over time, and the goal of a SPC tool called a control chart is...
Meta-analysis is a valuable tool to synthesize evidence and pool results from multiple sources. It plays an integral role in evidence-based medicine and may have a direct impact in the clinical setting. This dissertation explores several...
Multivariate linear models are commonly used for modeling the relationships between multiple responses and covariates. With OLS estimators, one can interpret the results in the analysis. However, the coefficient OLS estimates sometimes...
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.
