Browsing Biostatistics by Title
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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 ... 
An evaluation of saddlepoint approximations in the generalized linear model
(1996)Higher order asymptotic methods based on the saddlepoint approximation to a density provide fast and accurate approximate inference in a variety of situations. The double saddlepoint approximation to the exact conditional ... 
Evaluation of Strategies for the Phase II to Phase III Progression in Treatment Discovery
(20140430)The goal of clinical research is to improve the health of the population through the prevention, diagnosis, and treatment of disease. Clinical trials are essential for reliably evaluating a proposed treatment to determine ... 
Genome descent in isolated populations
(2001)An isolated population is one that is descended from a small group of individuals (founders), and in which population growth is due almost exclusively to births within the population, rather than immigration from outside. ... 
Graph Estimation and Cluster Analysis in High Dimensions
In many applications, it is of interest to uncover patterns from a highdimensional data set in which the number of features, p, is larger than the number of observations, n. We consider the areas of graph estimation and ... 
HosmerLemeshow goodnessoffit test: Translations to the Cox Proportional Hazards Model
(20130417)<bold>Background:</bold> The goodness of fit of a statistical model is commonly assessed by describing how well the model fits the observed data. For logistic regression the HosmerLemeshow goodnessoffit test compares ... 
Image analysis and signal extraction from cDNA microarrays
(2004)The emergence of microarray technology invariably leads to a discussion about data reliability amongst researchers. Many factors impact the accuracy of gene expression data gleaned from microarray experiments. These factors ...