Browsing Biostatistics by Title
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Assessing Vaccine Effects in HIV1 Vaccine Trials: Antigenic Maps, Antigen Selection, and Sieve Analysis
(20140224)The goal of vaccination against infectious disease is a net population effect on the risk of infection and/or disease progression. In HIV1 vaccine development efforts to date only a single HIV1 vaccine trial has shown ... 
The Bayesian Analysis of Data Arising from Complex Sampling Designs
(20130417)The majority of this thesis concerns the development of Bayesian methods for twophase studies. A twophase study is a study design in which limited information (including outcome) is known for a large "firstphase" study ... 
Bayesian estimation of participants’ adherence in an HIV prevention trial using multiple data sources and pharmacokinetic models
PreExposure Prophylaxis (PrEP) is an HIV prevention practice which uses antiretrovial drugs to keep HIVnegative individuals from infection with HIV. One of the antiretrovi ral drugs that is usually used for HIV treatment ... 
Bayesian Hierarchical Frailty Models for Heterogeneity in Risk
The effect of an intervention or exposure on timetoevent is most commonly estimated with the Cox model, which assumes proportional hazards. When heterogeneity in risk is present, the assumption of proportionality is ... 
Biostatistical Methods for HIV Monitoring and Prevention
Part I Pooledtesting methods can greatly reduce the number of tests needed to identify failures in a collection of samples. Existing methodology has focused primarily on binary tests, but there is a clear need for improved ... 
Causal inference in HIV vaccine trials: comparing outcomes in a subset chosen after randomization
(2005)In many experiments researchers would like to compare between treatments an outcome that only exists in a subset of participants selected after randomization. For example, in preventative HIV vaccine efficacy trials it is ... 
Causal Inference with Selection and Confounding Variables
Most complex observational and randomized studies are motivated by the potential of drawing causal statements. However, a usual statistical analysis may yield estimates that do not have causal interpretations. In fact, ... 
Causal mediation analysis with failure time outcome and errorprone longitudinal covariate
Mediation analyses are important for understanding the biological mechanisms whereby a treatment/exposure influences an outcome of interest. For example, one may be interested in whether body fat accumulation mediates an ... 
Challenges Associated with Statistical Analysis in the Presence of Sparse Data and Applications to Alternative Tobacco Product Research
(20130723)Rarely observed covariate combinations, or "sparsity" is a phenomenon associated with research concerning the health risks of alternativeuse (noncombusted tobacco products (AUPs)). Of particular concern is sparsity ... 
A Comparison of Sample Size Calculations for Cluster Randomized Crossover Trials with a Binary Outcome
A simplified sample size calculation for a cluster randomized crossover trial with a binary survival outcome (the “ TBOSS ” method) was compared to the closed form equation and simulation methods currently available from ... 
A comparison of three trough to peak estimators derived from ambulatory blood pressure data
(1997)A general multivariate model is proposed to analyze ABPM data obtained from multiple subjects in which two ABPM series, typically at baseline and on randomized therapy in a clinical trial, are obtained on each subject. The ... 
Covariate Measurement Error Correction Methods in Mediation Analysis with Failure Time Data
(20130417)Mediation analysis is important in understanding the mechanisms of one variable causing changes in another. Measurement error could be obscuring the ability of the potential mediator to explain this mechanism. Existing ... 
Dataadaptive Estimation in Longitudinal Data Structures with Applications in Vaccine Efficacy Trials
This dissertation develops methodology for dataadaptive estimation of parameters defined on longitudinal data structures, while this abstract serves as an introduction to the material covered herein. The dissertation is ... 
Disequilibrium finemapping of a rare allele via coalescent models of gene ancestry
(1998)Genetic linkage studies based on pedigree data have limited resolution, due to the relatively small number of segregations. Disequilibrium mapping, which uses population associations to infer the location of a disease ... 
Estimation and Comparison of HIVSpecific Substitution Matrices
Amino acid substitution matrices are commonly used for sequence alignment, phylogenetic inference and sequence comparison. Empirical organismspecific substitution matrices constructed using only sequence data from a ... 
Estimation and Conditional Inference in HighDimensional Statistical Models
In many areas of biology, recent advances in technology have facilitated the measurement of large numbers of features, while the number of observations in a data set may remain relatively modest. In this setting, lasso ... 
Estimators of Effect Modification of Cumulative Incidence: AalenJohansen and Targeted Minimum Lossbased Estimator
In time to event settings there are many occasions in which multiple events can occur. This competing risks phenomenon is often encountered in vaccine trials when interest is given to efficacy against a specific subtype ... 
Evaluating prediction performance of longitudinal biomarkers under cohort and twophase study designs
Risk prediction and evaluation of predictions based on longitudinal biomarkers are of interest in treatment selection, preventive medicine and management of chronic diseases. Methods to evaluate risk predictions in a ... 
An Evaluation of Adaptive Clinical Trial Designs with Prespecified Rules for Modifying the Sampling Plan
(20130225)Adaptive clinical trial design has been proposed as a promising new approach that may improve the drug discovery process. A comprehensive evaluation of adaptation should balance potential flexibility and efficiency gains ... 
Evaluation of Potential Surrogate Endpoints
(20130225)Valid surrogate endpoints can make clinical trials more efficient, allowing for more trials to be conducted and more rapid development of effective treatments. Identifying useful surrogates is a statistically challenging ...