Department of Statistics (MU): Recent submissions
Now showing items 120 of 99

Full Bayesian models for paired RNAseq data and Bayesian equivalence test
(University of MissouriColumbia, 2018)In my doctorate research, I have developed Bayesian models to analyze the paired RNAseq data for different types of design. The developed methods are especially of important practice for gene expression analysis using high ... 
Scalable Bayesian nonparametric learning for biomedical big data
(University of MissouriColumbia, 2018)Recent advances in arraybased and nextgeneration sequencing (NGS) technologies have revolutionized biomedical research, especially in cancer. The analysis of the datasets compiled from these technologies, usually referred ... 
Regression analysis of longitudinal covariates with censored and longitudinal outcome
(University of MissouriColumbia, 2018)Longitudinal data contain repeated measurements of variables on the same experimental subject. It is often of interest to analyze the relationship between these variables. Typically, there is one or several longitudinal ... 
Objective Bayesian analysis of the 2 x 2 contingency table and the negative binomial distribution
(University of MissouriColumbia, 2018)In Bayesian analysis, the “objective” Bayesian approach seeks to select a prior distribution not by using (often subjective) scientific belief or by mathematical convenience, but rather by deriving it under a prespecified ... 
Regression analysis of intervalcensored failure time data with non proportional hazards models
(University of MissouriColumbia, 2018)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Intervalcensored failure time data arises when the failure time of interest is known only to lie within an interval or window instead of being observed ... 
Bayesian hierarchical modeling of colorectal and breast cancer data in Missouri
(University of MissouriColumbia, 2018)Data on cancer in the United States is collected through cancer registries. The Missouri Cancer Registry and Research Center (MCRARC) maintains a statewide cancer surveillance system and participate in research in support ... 
A Bayesian classification framework with label corrections
(University of MissouriColumbia, 2014)The use of unlabeled data is very important for regression and classification analysis in many cases. However, the data may have an extra layer of complexity with some wrongly labelled data points. The traditional ... 
Semiparametric methods for regression analysis of panel count data and mixed panel count data
(University of MissouriColumbia, 2017)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Recurrent event data and panel count data are two common types of data that have been studied extensively in event history studies in literature. By ... 
Bayesian partition model for identifying hypo and hyper methylation
(University of MissouriColumbia, 2017)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This dissertation introduces MethyBayes, a full Bayesian partition model for identifying hypo and hypermethylated loci. The main interest of study on ... 
Some topics in multiregional clinical trials and metaanalysis using Bayesian models
(University of MissouriColumbia, 2017)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The dissertation consists of two distinct research topics. One is about sample size determination in MultiRegional Clinical Trials (MRCTs), the other ... 
Functional data analysis : children's mathematical development
(University of MissouriColumbia, 2016)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Bailey et al. (2014) suggested that children's mathematical development is related more to trait characteristics than to prior mathematical development. ... 
Bayesian analysis of fMRI data and RNASeq Time Course experiment data
(University of MissouriColumbia, 2015)The present dissertation contains two parts. In the first part, we develop a new Bayesian analysis of functional MRI data. We propose a novel triple gamma Hemodynamic Response Function (HRF) including the component to ... 
Semiparametric analysis of failure time data with complex structures
(University of MissouriColumbia, 2016)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Failure time data arise in many fields including biomedical studies and industrial life testing. Rightcensored failure time data are often observed ... 
Nonlocal priors for Bayesian variable selection in generalized linear models and generalized linear mixed models and their applications in biology data
(University of MissouriColumbia, 2016)A crucial problem in building a generalized linear model (GLM) or a generalized linear mixed model (GLMM) is to identify which subset of predictors should be included into the model. Hence, the main thrust of this dissertation ... 
Partially informative normal and partial spline models
(University of MissouriColumbia, 2015)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] There is a wellknown Bayesian interpretation of function estimation by spline smoothing using a limit of proper normal priors. This limiting prior has ... 
Bayesian smoothing spline models and their application in estimating yield curves
(University of MissouriColumbia, 2015)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The term structure of interest rates, also called the yield curve, is the series of interest rates ordered by term to maturity at a given time. The ... 
Bayesian hierarchical models for estimating nest survival
(University of MissouriColumbia, 2015)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Nest survival rate is a critical value in avian study to evaluate the landbirds populations. The widely used likelihoodbased logistic regression model ... 
A ballooned betalogistic model
(University of MissouriColumbia, 2015)The beta distribution is a simple and flexible model in which responses are naturally confined to the finite interval (0,1). Its parameters can be related to covariates such as dose and gender through a regression model. ... 
Bayesian hierarchical models for estimating nest survival
(University of MissouriColumbia, 2015)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Nest survival rate is a critical value in avian study to evaluate the landbirds populations. The widely used likelihoodbased logistic regression model ... 
Two sample inference for high dimensional mean with application to gene expression data
(University of MissouriColumbia, 2015)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Motivated by the gene expression analysis from biological science, we consider the two sample problem, where the number of variables is much larger ...