Now showing items 31-40 of 183
Statistical Methods for Aggregation of Indirect Information
How to properly aggregate indirect information is more and more important. In this dissertation, we will present two aspects of the issue: indirect comparison of treatment effects and aggregation of ordered-based rank data.
Methods for Analyzing Survival and Binary Data in Complex Surveys
Studies with stratified cluster designs, called complex surveys, have increased in popularity in medical research recently. With the passing of the Affordable Care Act, more information about effectiveness of treatment, ...
Revisiting Random Utility Models
This thesis explores extensions of Random Utility Models (RUMs), providing more flexible models and adopting a computational perspective. This includes building new models and understanding their properties such as ...
Retrospective Mixed Model and Propensity Score Methods for Case Control Data
In chapter one a Liability Threshold Mixed Linear Model (LTMLM) association statistic is introduced for ascertained case-control studies that increases power vs. existing mixed model methods for diseases with low prevalence, ...
Semiparametric Methods for Causal Mediation Analysis and Measurement Error
Chapter 1: Since the early 2000s, evidence has accumulated for a significant differential effect of first-line antiretroviral therapy (ART) regimens on human immunodeficiency virus (HIV) treatment outcomes, such as CD4 ...
Dilemmas in Design: From Neyman and Fisher to 3D Printing
This manuscript addresses three dilemmas in experimental design.
Interpretable and Scalable Bayesian Models for Advertising and Text
In the era of "big data", scalable statistical inference is necessary to learn from new and growing sources of quantitative information. However, many commercial and scientific applications also require models to be ...
Cell States and Cell Fate: Statistical and Computational Models in (Epi)Genomics
This dissertation develops and applies several statistical and computational methods to the analysis of Next Generation Sequencing (NGS) data in order to gain a better understanding of our biology. In the rest of the chapter ...
Integrated Analysis of Longitudinal Tumor Burden Data
The first part of this thesis introduces a new statistical method to estimate parameter values in a mixed population consisting of both single- and bi- phasic longitudinal trajectories. This pro- posed model is capable of ...
On Causal Inference for Ordinal Outcomes
This dissertation studies the problem of causal inference for ordinal outcomes. Chapter 1 focuses on the sharp null hypothesis of no treatment effect on all experimental units, and develops a systematic procedure for ...