Browsing Department of Statistical Sciences by Issue Date
Now showing items 1-20 of 54
-
Conjugate hierarchical models for spatial data: an application on an optimal selection procedure.
(2006-07-24)The theory of generalized linear models provides a unifying class of statistical distributions that can be used to model both discrete and continuous events. In this dissertation we present a new conjugate hierarchical ... -
Bayesian evaluation of surrogate endpoints.
(2006-07-29)To save time and reduce the size and cost of clinical trials, surrogate endpoints are frequently measured instead of true endpoints. The proportion of the treatment effect explained by surrogate endpoints (PTE) is a widely ... -
Bayesian adaptive designs for non-inferiority and dose selection trials.
(2006-07-31)The process of conducting a pharmaceutical clinical trial often produces information in a way that can be used as the trial progresses. Bayesian methods offer a highly flexible means of using such information yielding ... -
Bayesian inference for correlated binary data with an application to diabetes complication progression.
(2006-10-26)Correlated binary measurements can occur in a variety of practical contexts and afford interesting statistical modeling challenges. In order to model the separate probabilities for each measurement we must somehow account ... -
A restriction method for the analysis of discrete longitudinal missing data.
(2007-02-07)Clinical trial endpoints are traditionally either physical or laboratory responses. However, such endpoints fail to reflect how patients feel or function in their daily activities. Missing data is inevitable in most every ... -
Selected topics in statistical discriminant analysis.
(2007-02-07)This dissertation consists of three selected topics in statistical discriminant analysis: dimension reduction, regularization methods, and imputation methods. In Chapter 2 we first derive a new linear dimension-reduction ... -
Logistic regression with misclassified response and covariate measurement error: a Bayesian approach.
(2007-12-04)In a variety of regression applications, measurement problems are unavoidable because infallible measurement tools may be expensive or unavailable. When modeling the relationship between a response variable and covariates, ... -
Bayesian approaches to problems in drug safety and adaptive clinical trial designs.
(2008-06-10)The efficacy, safety, and cost of pharmaceutical products are critical issues in society today. Motivated both financially and ethically by these concerns, the pharmaceutical industry has continually worked to develop ... -
Sample size determination for Emax model, equivalence / non-inferiority test and drug combination in fixed dose trials.
(2008-06-11)Sample size determination is one of the most important aspects in clinical designs. Careful selection of appropriate sample sizes can not only save economic and human resources, but also improve model performance and ... -
Statistical monitoring of a process with autocorrlated output and observable autocorrelated measurement error.
(2008-06-11)Our objective in this work is to monitor a production process yielding output that is correlated and contaminated with autocorrelated measurement error. Often, the elimination of the causes of the autocorrelation of the ... -
Logistic regression with covariate measurement error in an adaptive design : a Bayesian approach.
(2008-10-14)Adaptive designs are increasingly popular in clinical trials. This is because such designs have the potential to decrease patient exposure to treatments that are less efficacious or unsafe. The Bayesian approach to ... -
Bayesian and maximum likelihood methods for some two-segment generalized linear models.
(2008-10-14)The change-point (CP) problem, wherein parameters of a model change abruptly at an unknown covariate value, is common in many fields, such as process control, epidemiology, and ecology. CP problems using two-segment ... -
Semiparametric AUC regression for testing treatment effect in clinical trial.
(2008-10-15)We investigated distribution free methods for testing covariate adjusted treatment effects. Dodd and Pepe (2003) proposed a semiparametric logistic regression model for the area under the ROC curve (AUC). Their model ... -
Statistical considerations in the analysis of multivariate Phase II testing.
(2009-04-01)In medical diagnosis and treatment, many diseases are characterized by multiple measurable differences in clinical (e.g., physical or radiological differences) and laboratory parameters (biomarkers from "healthy levels". ... -
Bayesian and pseudo-likelihood interval estimation for comparing two Poisson rate parameters using under-reported data.
(2009-04-01)We present interval estimation methods for comparing Poisson rate parameters from two independent populations with under-reported data for the rate difference and the rate ratio. In addition, we apply the Bayesian paradigm ... -
Bayesian sample-size determination and adaptive design for clinical trials with Poisson outcomes.
(Elsevier., 2010)Because of the high cost and time constraints for clinical trials, researchers often need to determine the smallest sample size that provides accurate inferences for a parameter of interest or need to adaptive design ... -
Topics in dimension reduction and missing data in statistical discrimination.
(2010-02-02)This dissertation is comprised of four chapters. In the first chapter, we define the concept of linear dimension reduction, review some popular linear dimension reduction procedures, discuss background research that we ... -
Lectio divina.
(2010-06-23)Lectio Divina is a musical exploration of the contemplative prayer and scripture‐reading practice called "Lectio Divina". The work is written for a chamber ensemble: flute, clarinet, violin, cello, piano and percussion. ... -
Count regression models with a misclassified binary covariate : a Bayesian approach.
(2010-06-23)Mismeasurment, and specifically misclassification, are inevitable in a variety of regression applications. Fallible measurement methods are often used when infallible methods are either expensive or not available. Ignoring ... -
Bayesian models for discrete censored sampling and dose finding.
(2010-06-23)We first consider the problem of discrete censored sampling. Censored binomial data may lead to irregular likelihood functions and problems with statistical inference. We consider a Bayesian approach to inference for ...