Browsing by Author "Seaman, John Weldon, 1956-"
Now showing items 1-20 of 23
-
Bayesian adaptive designs for non-inferiority and dose selection trials.
Spann, Melissa Elizabeth. (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 and maximum likelihood methods for some two-segment generalized linear models.
Miyamoto, Kazutoshi. (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 ... -
Bayesian approaches to correcting bias in epidemiological data.
Bennett, Monica M. (2011-05-12)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.
Mauldin, Jo A. (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 ... -
Bayesian evaluation of surrogate endpoints.
Feng, Chunyao. (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 inference for correlated binary data with an application to diabetes complication progression.
Carlin, Patricia M. (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 ... -
Bayesian methods for hurdle models.
Cheng, Joyce H., 1986- (2015-02-09)Hurdle models are often presented as an alternative to zero-inflated models for count data with excess zeros. They consist of two parts: a binary model indicating a positive response (the “hurdle”) and a zero-truncated ... -
Bayesian methods in non-clinical pharmaceutical statistics.
Faya, Paul. 1979- (2017-03-17)This dissertation is composed of three research papers investigating the application of Bayesian methods to pharmaceutical non-clinical statistics. In the first paper, we present an application of Bayesian assurance and ... -
Bayesian methods to estimate the accuracy of diagnostic tests in meta-analysis models.
Knorr, Jack S. (, 2014-09-05)With the growing number of studies looking at the performance of diagnostic tests, combining the studies into a meta-analysis becomes an important and increasingly viable area of statistics, especially within the medical ... -
Bayesian modelling of mixed outcome types using random effect.
Wei, Hua, 1982- (2012-11-29)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.
Pruszynski, Jessica E. (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 ... -
A bivariate regression model with correlated mixed responses.
Bray, Ross A. (, 2013-09-16)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 ... -
Contributions to the theory and practice of prior elicitation in biopharmaceutical research.
Blair, Somer. 1987- (2017-04-11)In this dissertation, we consider modeling problems in biopharmaceutical research, much of which is motivated by industry colleagues. Expert opinion is necessary in many applications of survival analysis, especially in ... -
Count regression models with a misclassified binary covariate : a Bayesian approach.
Morgan-Cox, MaryAnn. (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 ... -
Interval-censored negative binomial models : a Bayesian approach.
Doherty, Stephanie Michelle. (, 2012-11-29)Count data are quite common in many research areas. Interval-censored counts, in which an interval representing a range of counts is observed rather than the precise count, may arise in many situations, including survey ... -
Logistic regression models for short sequences of correlated binary variables possessing first-order Markov dependence.
Marcovitz, Michelle S.; 0000-0002-0871-0897 (2015-07-23)In this dissertation we consider a first-order Markov dependence model for a short sequence of correlated Bernoulli random variables. Specifically, we offer logistic regression models with first-order Markov dependency, ... -
Logistic regression with covariate measurement error in an adaptive design : a Bayesian approach.
Crixell, JoAnna Christine, 1979- (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 ... -
Logistic regression with misclassified response and covariate measurement error: a Bayesian approach.
McGlothlin, Anna E. (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, ... -
Poisson regression models for interval censored count data.
Watson, Sydeaka P. (2011-05-12)In this dissertation, we develop Bayesian models for interval censored Poisson counts in the presence of zero inflation and missing data. As a motivating example, we consider data arising from a Human Immunodeficiency Virus ... -
A restriction method for the analysis of discrete longitudinal missing data.
Moore, Page Casey. (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 ...