Biostatistics
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Evaluation of Prediction Performance Metrics in the Rare Event Setting
Area under the receiving operator characteristic curve (AUC) is a commonly reported measure of discriminative performance for binary prediction models. However, there are concerns about AUC being a misleading measure of ... -
Statistical Methods for Association Analysis of Microbiome Data
The human microbiome is an integral component of the human body. High-throughput sequencing techniques have provided detailed information on abundance and phylogeny of individual taxa in the human microbiome. A variety of ... -
Behavioral Carry-Over Effects and Power Considerations in Crossover Trials
The carry-over effect remains an outstanding concern in crossover trials when washout periods cannot sufficiently diminish their impacts. This can occur in comparative effectiveness research where carry-over effects are ... -
Neural Networks as Tools for Posterior Estimation and Inference
In this dissertation, we will discuss three applications for neural networks in the paradigm of Bayesian estimation and inference. In Chapter 2, we describe a likelihood-free method of estimating posterior quantiles using ... -
Reframing Cox Proportional Hazards Model for Big Data and Neural Networks
In many medical and biomedical applications, we measure the outcome as a “time-to-event” (e.g., disease progression or death). The aim of this dissertation is to propose frameworks for survival analysis and prediction with ... -
Generalization of kernel machine methods for association testing of multi-omics data
Over the past couple of decades, genome-wide association studies (GWASs) have successfully identified thousands of loci associated with complex traits and diseases in humans. Despite the immense success of these statistical ... -
Measurement Error in Microbiome Sequencing Experiments: Statistical and Scientific Considerations
Next-generation sequencing (NGS)methods have become an essential tool in the study of complex microbial communities known as microbiomes. Because their near ubiquity, such communities have been the focus of substantial ... -
Statistical Methods for Human Rights and Child Mortality Estimation
This dissertation addresses statistical methodology commonly used in human rights research and child mortality estimation. We first consider two related problems, record linkage and multiple-systems estimation, typically ... -
Methods for the design and analysis of stepped wedge trials under model misspecification
This dissertation consists of three projects that attempt to address issues related to the design and analysis of stepped wedge trials (SWTs). Stepped wedge trials (SWTs) are a type of cluster-randomized trial that are ... -
Statistical methods for the analysis of spatial gene expression data
In recent years, there has been rapid development of spatial gene expression and spatial transcriptomics technologies, though corresponding advances in computational and statistical tools for the analysis of the data ... -
Novel data-adaptive multivariate testing procedures, with applications to HIV research
Project 1: Construct a generic data-adaptive framework for multivariate point null testing.Specifically, a data-driven optimality criterion is proposed for selecting among a large collection of candidate test statistics. ... -
Penalized discriminant analysis for multivariate functional data
We introduce a penalized discriminant analysis method for multivariate functional data supported on compact 1D domains, motivated by an application that aims to identify subjects with poor cognitive status from diffusion ... -
Statistical Methods for Problems in Heterogeneous Populations, from Clinical Trials to Latent-Variable Models
This dissertation provides methods for analyzing data from heterogeneous populations and addresses the problems of relative efficiency estimation, estimation in Markov-switching vector autoregressive models, and statistical ... -
Statistical tools for the multi-omics analysis of microbiome data
The human microbiome consists of trillions of bacteria, archaea, and viruses that exist on virtually every organ in the body. The microbiome plays a fundamental role in human health and has been implicated in several ... -
Testing for a difference in means after selection
In modern data analysis, we often want to test for a difference in means between groups selected based on the observed data. This is a challenging task: when the null hypothesis is selected based on the data, classical ... -
Modeling multivariate health and demographic outcomes in low- and middle-income countries using sample registration and complex survey data
Improving the health of the most disadvantaged populations requires obtaining reliable health and demographic indicators in order to inform policy and interventions. Unfortunately, the low- and middle-income countries with ... -
Modern Sieve Estimators for Nonparametric Problems: Streaming Data and High-dimensional Data
Estimation of a regression function, linking a set of features to an outcome of interest, is a fundamental statistical task. This dissertation focuses on the application of sieve estimators in modern statistical learning ... -
Novel data-adaptive statistical methods for observational and experimental studies with applications to HIV/AIDS research
Data-adaptive statistical methods can often be used to improve different attributes of estimators, such as their asymptotic variance, calibration, and predictive accuracy. In this dissertation, we (i) describe how careful ... -
Methods for Coherent and Exact Inference
This dissertation provides methods for coherent and exact inference for two types of problems in statistics. The first problem provides coherent criteria for the testing of nested interval null hypothesis. The second and ... -
Statistical Methods for Transcriptome-Wide Association Studies in Ancestrally Diverse Populations
Transcriptome-wide association studies (TWAS) have become more commonly used in recent years. TWAS integrate genome-wide association studies (GWAS) with gene expression mapping studies in order to identify genes whose gene ...
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