Browsing Biostatistics by Title
Now showing items 1-20 of 215
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A computational pipeline for identifying copy number variation from single nucleotide polymorphism data and applications to congenital heart disease
Copy number variants (CNVs) are duplications or deletions of regions of the genome. CNVs, similar to single nucleotide variants (SNVs), range in frequency and severity in their effects on human disease. Despite the likely ... -
A Decision Theoretic Framework for Hypothesis and Significance Testing
From its inception, statistical testing has been a controversial area. There are several philosophies of testing and inference, the most common among them being the so-called frequentist and Bayesian approaches. These ... -
A Deep Learning Approach to Infer Cellular Features from Pathology Imaging Data
Recent developments in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) provide unprecedented opportunities for studying individual cells and their organization. While these techniques are underutilized ... -
A Finite Approximation Framework for Infinite Dimensional Functional Problems
It is often of interest to non-parametrically estimate regression functions. Penalized regression (PR) is one effective, well-studied solution to this problem. Unfortunately, in many cases, finding exact solutions to PR ... -
A Method for Clustering Flexible Longitudinal Trajectories with An Application to An HIV Prevention Trial
Dapivirine (25 mg) in a silicone elastomer Vaginal Ring is a safe and effective method to prevent HIV-1 infection in healthy, sexually active, HIV-negative women. Understanding women’s adherence to the dapivirine vaginal ... -
A method for quantifying the regression to the mean effect applied to bivariate binary outcomes in the presence of limited baseline data
In studies lacking a control group, a crucial step in estimating the study effect is to tease apart the proportion of the total observed change in key outcomes which are due to study participation, from that which is caused ... -
A Novel Analysis of Accelerometry Data: Calibration and Flexible Association Modeling in an Epidemiological Study of Older Women
Accelerometers have been widely deployed to objectively measure and monitor physical activity and sedentary behavior in large epidemiological studies. The traditional summary metric, known as counts, summarizes raw ... -
A Power Transformation-based Compositional Data Analysis Approach with Application to Physical Activity Epidemiology
Compositional data arise in many scientific fields, where relative proportions of different parts of a whole are basic units of data. An example is physical activity (PA) epidemiology, where one is often interested in ... -
A Simpler Model for the Impact of Atrial Fibrillation on Cognitive Trajectories in the Elderly
In their 2013 paper “Atrial fibrillation and cognitive decline: A longitudinal cohort study”, Dr. Thacker and colleagues investigated whether, in the absence of clinical stroke, incident atrial fibrillation was associated ... -
A Simulation Study of Statistical Approaches to Data Analysis in the Stepped Wedge Design
This paper studies model-based and permutation-based approaches to analyze data in the stepped wedge design under 9 scenarios. We compare robustness, efficiency, Type I error rate under null conditions, and power under ... -
A simulation study to evaluate the effect of constrained randomization for the design and analysis of stepped wedge cluster-randomized trials
In this study, we conducted simulations to evaluate the effect of constrained randomization on testing the treatment effect in terms of type I error and power with data generated from a stepped wedge cluster-randomized ... -
A Statistical Method for Analyzing Risk Difference in Trials with a Three-Level Paired Design
This thesis is motivated from an animal trial for a wearable external cardiac defibrillator. Each pig in the trial will be treated with two devices (test vs. control) after induced to experience ventricular fibrillation ... -
A unified approach to model-agnostic variable importance
Assessing the relative contribution of subsets of features towards predicting the response is often of interest in predictive modeling applications; this contribution is typically referred to as variable importance. Often, ... -
Accounting for subject-level heterogeneity in sieve analysis of vaccine efficacy
In randomized trials of preventative vaccines, sieve analysis tests whether vaccine efficacy differs by a characteristic of the disease endpoint. These methods often assume a leaky model, in which treatment proportionally ... -
Accounting for the Presence of Surrogate Data in Adaptive Clinical Trials
Some adaptive designs for randomized clinical trials (RCTs) allow for flexibility in modifying the sequential sampling plan using results from unblinded interim analyses. However, care must be taken to ensure that desired ... -
Adapting Statistical Learning Method for Spatial Applications
In this dissertation, we develop new principled applications of statistical learning methods in spatial applications. In the first chapter, we consider a modified regression tree approach allowing for spatial correlation ... -
Adaptive designs in the time to event setting: The potential for benefit and risk
Group sequential designs (GSDs) have been the standard sequential approach to maintain scientific, ethical, and efficiency goals in any confirmatory Phase III studies. Over the past two decades, adaptive extensions to group ... -
Adaptive Randomization Ratios in Multi-arm Clinical Trials
Ethics and economics are two of many motivations for streamlining the process of discovering new therapies for the treatment of human disease. Population ethics and economics dictate that any true benefit be demonstrated ... -
Adaptive Statistical Inference Procedures for Multigroup Data and Phylogenetic Tree Inferences
Multigroup data is a common data type in fields such as biology, the environmental sciences and the social sciences. This dissertation focuses on developing new statistical methodologies for multigroup data analysis. When ... -
Additive hazards regression with incomplete covariate data
(1997)This dissertation addresses two incomplete covariate data problems in the additive hazards (AH) regression model for failure time data. Both are examples of two-phase designs where some covariate is measured only on a ...