Biostatistics Commons^™

A Predictive Probability Interim Design For Phase Ii Clinical Trials With Continuous Endpoints, Meng Liu

Theses and Dissertations--Epidemiology and Biostatistics

Phase II clinical trials aim to potentially screen out ineffective and identify effective therapies to move forward to randomized phase III trials. Single-arm studies remain the most utilized design in phase II oncology trials, especially in scenarios where a randomized design is simply not practical. Due to concerns regarding excessive toxicity or ineffective new treatment strategies, interim analyses are typically incorporated in the trial, and the choice of statistical methods mainly depends on the type of primary endpoints. For oncology trials, the most common primary objectives in phase II trials include tumor response rate (binary endpoint) and progression disease-free survival …

Statistical Analyses To Detect And Refine Genetic Associations With Neurodegenerative Diseases, Yuriko Katsumata

Theses and Dissertations--Epidemiology and Biostatistics

Dementia is a clinical state caused by neurodegeneration and characterized by a loss of function in cognitive domains and behavior. Alzheimer’s disease (AD) is the most common form of dementia. Although the amyloid β (Aβ) protein and hyperphosphorylated tau aggregates in the brain are considered to be the key pathological hallmarks of AD, the exact cause of AD is yet to be identified. In addition, clinical diagnoses of AD can be error prone. Many previous studies have compared the clinical diagnosis of AD against the gold standard of autopsy confirmation and shown substantial AD misdiagnosis Hippocampal sclerosis of aging (HS-Aging) …

Informational Index And Its Applications In High Dimensional Data, Qingcong Yuan

Theses and Dissertations--Statistics

We introduce a new class of measures for testing independence between two random vectors, which uses expected difference of conditional and marginal characteristic functions. By choosing a particular weight function in the class, we propose a new index for measuring independence and study its property. Two empirical versions are developed, their properties, asymptotics, connection with existing measures and applications are discussed. Implementation and Monte Carlo results are also presented.

We propose a two-stage sufficient variable selections method based on the new index to deal with large p small n data. The method does not require model specification and especially focuses …

Family-Based Association Studies Of Autism In Boys Via Facial-Feature Clusters, Luke Andrew Settles

Masters Theses

"Autism spectrum disorder (ASD) refers to a set of developmental disorders with varied attributes. Due to its substantial heterogeneity in terms of behavioral and clinical phenotypes, it is challenging to discern the genetic biomarkers behind ASD, even though the disease is known to be genetic in nature. This serves as a motivation to detect relationships between single nucleotide polymorphisms (SNPs) and a causal autism disease susceptibility locus (DSL) within more homogeneous subgroups. Recently, clinically meaningful subclassifications of ASD have been discovered utilizing facial features of prepubescent boys. Therefore, through the employment of data from 44 prepubertal Caucasian boys with ASD …

Analysis Of Data From A Study To Identify Potential Biomarkers To Indicate Renal Injury, Mitchell D. Tahtinen

Dissertations, Master's Theses and Master's Reports

Ureteropelvic junction obstruction is a disease in which flow from the kidney to the bladder is obstructed for extended periods of time causing irreversible damage to the kidney. Current tests to detect kidney damage caused by obstruction are not effective until significant damage occurs. The purpose of this report is to identify a panel of biomarkers in urine to detect kidney damage earlier by analyzing data collected from a two-part study. Currently, two established urinary biomarkers to indicate kidney damage are NGAL and KIM-1. Biomarkers of interest in this study are CD13, CD10, and CD26. Results from the linear mixed …

The Generalized Monotone Incremental Forward Stagewise Method For Modeling Longitudinal, Clustered, And Overdispersed Count Data: Application Predicting Nuclear Bud And Micronuclei Frequencies, Rebecca Lehman

Theses and Dissertations

With the influx of high-dimensional data there is an immediate need for statistical methods that are able to handle situations when the number of predictors greatly exceeds the number of samples. One such area of growth is in examining how environmental exposures to toxins impact the body long term. The cytokinesis-block micronucleus assay can measure the genotoxic effect of exposure as a count outcome. To investigate potential biomarkers, high-throughput assays that assess gene expression and methylation have been developed. It is of interest to identify biomarkers or molecular features that are associated with elevated micronuclei (MN) or nuclear bud (Nbud) …

Longitudinal And Geographical Modeling Of Circular Data With An Application To Sudden Infant Death Syndrome, Xinyan Cai

Theses and Dissertations

The aim of this thesis is to study seasonality of death in U.S. infants who died from SIDS. We also propose to investigate secular trends and geographical patterns of seasonal patterns of mortality. The application of circular statistics is used to describe the seasonality of the month of death in infants who died from SIDS in 1990, 2000 and 2010. The secular trends of seasonal patterns of SIDS mortality are investigated using a circular linear regression model after adjusting for potential confounders. The geographical variation in seasonal patterns of SIDS mortality is explored from the U.S. map and quantified by …

Statistical Methods For Multivariate And Correlated Data, Xinling Xu

Theses and Dissertations

A commonly encountered data type in real life is count data, especially in selfreported behavioral studies. One issue of the self-reported count data is the inaccuracy. In the first part of the dissertation, we are going to address one specific type of inaccuracy in bivariate count data–heaping. Copula functions are used for the formulation of the bivariate distribution. Using copula functions for solving data inaccuracy problems is still a new area, which we are going to explore in this dissertation.

We also discuss the methods for variable selection when the explanatory variables are highly correlated. In particular, our method is …

Evaluation Of Goodness-Of-Fit Tests For The Cox Proportional Hazards Model With Time-Varying Covariates, Shanshan Hong

Theses and Dissertations

The proportional hazards (PH) model, proposed by Cox (1972), is one of the most popular survival models for analyzing time-to-event data. To use the PH model properly, one must examine whether the data satisfy the PH assumption. An alternative model should be suggested if the PH assumption is invalid. The main purpose of this thesis is to examine the performance of five existing methods for assessing the PH assumption. Through extensive simulations, the powers of five different existing methods are compared; these methods include the likelihood ratio test, the Schoenfeld residuals test, the scaled Schoenfeld residuals test, Lin et al. …

Marginal Structural Cox Model For Survival Data With Treatment-Confounder Feedback, Yanan Zhang

Theses and Dissertations

In an observational longitudinal study, there can be time-varying exposure/treatment and time-varying confounders. When the confounders affect the exposure and prior exposure also has an impact on levels of confounders, there is treatment confounder feedback. To admit estimation of unbiased causal effects, these conditions need to be hold, exchangeability, positivity, consistency. The traditional method of conditioning on potential confounders does not meet these 3 conditions. Therefore, parameter estimates from traditional Cox model are biased casual effect estimates when the treatment confounder feedback exists. The marginal structural Cox model can be used to address this issue. By calculating and including inverse …

Comparing The Structural Components Variance Estimator And U-Statistics Variance Estimator When Assessing The Difference Between Correlated Aucs With Finite Samples, Anna L. Bosse

Theses and Dissertations

Introduction: The structural components variance estimator proposed by DeLong et al. (1988) is a popular approach used when comparing two correlated AUCs. However, this variance estimator is biased and could be problematic with small sample sizes.

Methods: A U-statistics based variance estimator approach is presented and compared with the structural components variance estimator through a large-scale simulation study under different finite-sample size configurations.

Results: The U-statistics variance estimator was unbiased for the true variance of the difference between correlated AUCs regardless of the sample size and had lower RMSE than the structural components variance estimator, providing better type 1 error …

Weighted Quantile Sum Regression For Analyzing Correlated Predictors Acting Through A Mediation Pathway On A Biological Outcome, Bhanu M. Evani

Theses and Dissertations

Abstract

Weighted Quantile Sum Regression for Analyzing Correlated Predictors Acting Through a Mediation Pathway on a Biological Outcome

By

Bhanu M. Evani, Ph.D.

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University.

Virginia Commonwealth University, 2017.

Major Director: Robert A. Perera, Asst. Professor, Department of Biostatistics

This work examines mediated effects of a set of correlated predictors using the recently developed Weighted Quantile Sum (WQS) regression method. Traditionally, mediation analysis has been conducted using the multiple regression method, first proposed by Baron and Kenny (1986), which has since …