Search
Now showing items 211-220 of 229
Variational inference in high-dimensional Bayesian regression models
(2024-04-26)
In modern applications of Bayesian Statistics, the posterior distribution is typically high-dimensional and analytically intractable. Variational Inference (VI) has emerged as an attractive option to approximate these ...
Essays in Econometrics
(2024-03-26)
This dissertation consists of three essays in econometrics. A common throughline is decision theory, defined here broadly as the formal considerations justifying, informing, or undermining choices of statistical procedures.
The ...
Large Scale Inference and Combinatorial Variable Selection for Complex Dataset
(2024-04-30)
This dissertation advances the field of modern statistical theory and methodology by focusing on two primary areas: first, the quantification of uncertainty beyond mere estimation in combinatorial inference theory; and ...
Design-Based Causal Inference: Applications to Social Sciences and Industry
(2024-04-12)
In today's data-driven world, social scientists and industry data scientists increasingly utilize larger-scale complex experiments, e.g., adaptive sequential experiments and high-dimensional treatments, and novel observational ...
Methods for the Design and Analysis of Clinical Trials: Uncertainty Directed Randomization and Data Synthesis
(2023-11-21)
Randomized trials are one of society's most powerful tools for testing novel therapeutics. There are both ethical imperatives and economic incentives to ensure that their design and analysis is as efficient as possible. ...
Health Care Variation and Its Determinants: Studies on Physician Quality, Cancer Screening, and Cardiovascular Care
(2024-03-12)
This dissertation investigates drivers of variation in health care utilization and quality, with a focus on physician decision-making and patient outcomes. The first chapter examines the distribution of new physician quality ...
Systematically inferring directional effects within cell states from single-cell data
(2023-08-28)
A deeper understanding of the molecular wiring of cells in health—and where it goes awry in disease—can enable the development of more precise therapies that target not just consequences, but also the root causes of ...
Nonparametric Methods for Building and Evaluating Models of Biological Sequences
(2023-07-25)
Probabilistic models of biological sequences are used to design drugs, make predictions about human health, and learn basic biology. Sequence data is high dimensional so a probabilistic model must make biological assumptions ...
Essays on Health Policy Methods
(2021-07-12)
This dissertation includes 4 chapters on methods for health policy research. In the first 3 chapters, we consider common approaches to observational policy analyses. We discuss statistical and practical problems with the ...
Statistical Models of the Spatial, Kinematic, and Chemical Complexity of Dust
(2024-05-06)
Dust in the interstellar medium (ISM) impacts almost every astronomical observation. In this thesis, I describe how we can characterize the distribution and properties of dust based on its contribution to images and spectra ...