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Topics in Causal Inference and the Law
(2018-04-13)
Randomized experiments are a fundamental tool for estimating the causal effects of proposed interventions. While analysis of some experiments can be quite straightforward, other experiments may present difficult analytical ...
Inference for Incomplete Data and Dependent Data
(2018-05-15)
This thesis is about statistical inference on two classes of data: incomplete data (Chapters 1, 2 and 3) and dependent data (Chapter 4). Chapter 2 relaxes one crucial assumption made in Chapter 1, and then Chapter 3 further ...
Statistical Methods for Evidence Synthesis
(2018-08-31)
In many empirical disciplines, scientific discovery is modularized into discrete papers each investigating one or more hypotheses. Synthesizing these modules of evidence is critical to inform a balanced and appropriately ...
Essays in Time Series Econometrics
(2018-04-23)
In this dissertation, I address issues related to both statistical and causal inference in time series in three independent chapters.
In the first chapter, coauthored with E. Lazarus and J. H. Stock, we use higher-order ...
Low-Resolution Statistical Modeling With Belief Functions
(2018-05-11)
This dissertation addresses problems in the theoretical, methodological, and computational aspects of statistical modeling in the presence of low-resolution information. I consider a structural kind of model uncertainty ...
Physician Preferences for Medical Innovation
(2018-05-15)
Health care spending growth challenges the budgets of governments, businesses, and families. In 2015, one in every six dollars spent in the U.S. economy was related to health care – twice the share in 1980. The rapid growth ...
Leveraging Functional Annotations and Multiethnic Data to Improve Polygenic Risk Prediction
(2018-09-25)
Polygenic risk prediction is a widely-investigated topic because of its potential clinical application as well as its utility to have a better understanding of the genetic architecture of complex traits. Methods to perform ...
New Statistical Methods for Integrative Data Analysis and Applications in Biology, Epidemiology and Finance
(2018-09-06)
This dissertation consists of four self-contained chapters where statistical methods for integrative data analysis with applications in biology, epidemiology and finance are introduced and discussed. Chapters 1 and 2 focus ...
Counting Stars: Developing Probabilistic Cataloging for Crowded Fields
(2018-05-09)
The depth of next generation surveys poses a great data analysis challenge: these surveys will suffer from crowding, making their images difficult to deblend and catalog. Sources in crowded fields are extremely covariant ...
Dealing with Interference on Experimentation Platforms
(2018-09-16)
The theory of causal inference, as formalized by the potential outcomes framework, relies on an assumption that the experimental units are independent. When independence is not tenable, we say there is interference, and ...