Now showing items 1-10 of 184
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 ...
A Bayesian Perspective on Factorial Experiments Using Potential Outcomes
Factorial designs have been widely used in many scientific and industrial settings, where it is important to distinguish "active'' or real factorial effects from "inactive" or noise factorial effects used to estimate ...
Advances in the Normal-Normal Hierarchical Model
This thesis consists of results relating to the theoretical and computational advances in modeling the Normal-Normal hierarchical model.
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, ...
Capture-recapture Estimation for Conflict Data and Hierarchical Models for Program Impact Evaluation
A relatively recent increase in the popularity of evidence-based activism has created a higher demand for statisticians to work on human rights and economic development projects. The statistical challenges of revealing ...
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 ...
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 ...
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.
Complications in Causal Inference: Incorporating Information Observed After Treatment is Assigned
Randomized experiments are the gold standard for inferring causal effects of treatments. However, complications often arise in randomized experiments when trying to incorporate additional information that is observed after ...
Core-collapse Supernova Progenitors in the Era of Untargeted Transient Searches
Core-collapse supernovae (SNe) are the highly energetic explosions of massive stars (> 8 solar masses) that are pervasive in their influence throughout astrophysics. They are the phenomenon with primary responsibility for ...