Browsing Department of Statistical Sciences by Title
Now showing items 120 of 42

Bayesian adaptive designs for noninferiority and dose selection trials.
(20060731)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 and likelihoodbased interval estimation for the risk ratio using double sampling with misclassified binomial data.
(20110105)We consider the problem of point and interval estimation for the risk ratio using double sampling with twosample misclassified binary data. For such data, it is wellknown that the actual data model is unidentifiable. To ... 
Bayesian and maximum likelihood methods for some twosegment generalized linear models.
(20081014)The changepoint (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 twosegment ... 
Bayesian and pseudolikelihood interval estimation for comparing two Poisson rate parameters using underreported data.
(20090401)We present interval estimation methods for comparing Poisson rate parameters from two independent populations with underreported data for the rate difference and the rate ratio. In addition, we apply the Bayesian paradigm ... 
Bayesian approaches for design of psychometric studies with underreporting and misclassification.
(, 20130515)Measurement error problems in binary regression are of considerable interest among researchers, especially in epidemiological studies. Misclassification can be considered a special case of measurement error specifically ... 
Bayesian approaches to correcting bias in epidemiological data.
(20110512)Bias in parameter estimation of count data is a common concern. The concern is even greater when all counts are not recorded. Failing to adjust for underreported data can lead to incorrect parameter estimates. A Bayesian ... 
Bayesian approaches to problems in drug safety and adaptive clinical trial designs.
(20080610)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 ... 
Bayesian evaluation of surrogate endpoints.
(20060729)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 inference for correlated binary data with an application to diabetes complication progression.
(20061026)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 ... 
Bayesian methods to estimate the accuracy of a binary measurement system.
(20160419)Binary Measurement Systems (BMS) are frequently used in such applications as quality control. They are important enough that their operating characteristics, the repeatability and reproducibility are important because of ... 
Bayesian modelling of mixed outcome types using random effect.
(20121129)The problem of analyzing associated outcomes of mixed type arises frequently in practice. In this dissertation we develop several Bayesian models for analyzing associated discrete and continuous responses simultaneously ... 
Bayesian models for discrete censored sampling and dose finding.
(20100623)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 ... 
Bayesian models for unmeasured confounder in the analysis of timetoevent data.
(20160323)Observational studies that omit confounders are subject to bias. In this dissertation we consider the specific case of timetoevent data. We also provide both the Bayesian parametric and the semiparametric “twin regression” ... 
Bayesian samplesize 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 ... 
Bayesian topics in biostatistics : treatment selection, sample size, power, and misclassification.
(, 20111219)Bayesian methodology is implemented to investigate three problems in biostatistics. The first problem considers using biomarkers to select optimal treatments for individual patients. A Bayesian adaptation of the selection ... 
A bivariate regression model with correlated mixed responses.
(, 20130916)In the dissertation we consider a bivariate model for associated binary and continuous responses such as those in a clinical trial where both safety and efficacy are observed. We designate a marginal and conditional model ... 
Conjugate hierarchical models for spatial data: an application on an optimal selection procedure.
(20060724)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 ... 
Count regression models with a misclassified binary covariate : a Bayesian approach.
(20100623)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 ... 
Interval estimation for TPRs and FPRs of two diagnostic tests with unverified negatives.
(20110512)In the clinical setting, the performance of a diagnostic or screening test is often summarized using the test's true positive rate (TPR) and false positive rate (FPR). However, estimation of the TPR and FPR for a diagnostic ... 
Intervalcensored negative binomial models : a Bayesian approach.
(, 20121129)Count data are quite common in many research areas. Intervalcensored counts, in which an interval representing a range of counts is observed rather than the precise count, may arise in many situations, including survey ...