Now showing items 1-10 of 129
Evaluating Intended and Unintended Consequences of Health Policy and Regulation in Vulnerable Populations
The objective of this dissertation is to evaluate whether two different types of policy interventions in the United States are associated with health service utilization and economic outcomes. Paper 1: The number of ...
Estimating Individual Causal Effects
Most empirical work focuses on the estimation of average treatment effects (ATE). In this dissertation, I argue for a different way of thinking about causal inference by estimating individual causal effects (ICEs). I ...
Rich Linguistic Structure from Large-Scale Web Data
The past two decades have shown an unexpected effectiveness of Web-scale data in natural language processing. Even the simplest models, when paired with unprecedented amounts of unstructured and unlabeled Web data, have ...
Dilemmas in Design: From Neyman and Fisher to 3D Printing
This manuscript addresses three dilemmas in experimental design.
Post-Genomic Approaches to Personalized Medicine: Applications in Exome Sequencing, Microbiome, and COPD
Since the completion of the sequencing of the human genome at the turn of the century, genomics has revolutionized the study of biology and medicine by providing high-throughput and quantitative methods for measuring ...
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, ...
Topics in experimental and tournament design
We examine three topics related to experimental design in this dissertation. Two are related to the analysis of experimental data and the other focuses on the design of paired comparison experiments, in this case knockout ...
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 ...
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.
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 ...