Time introduces complexity in causal inference for observational studies. This thesis investigates two sources of bias for studies involving time-varying data. One is the missing …
Provider profiling is used to gauge the level of care that is being offered across providers. The extensive repercussions of provider profiling on the health …
This thesis work is motivated by the specific challenges in analyzing data from clinical trials in behavioral medicine. Specifically, smoking cessation and physical activity trials. …
Abstract of Analysis of temporal trends in opioid prescribing: Assessing the Effectiveness of an opioid prescribing policy using segmented regression, difference in difference versus propensity …
Randomized controlled trials (RCTs) are often considered the gold standard for investigating the effects of an intervention. However, selective recruitment criteria often exclude vulnerable populations …
In practice, it is rare that the true generating mechanism of a data source is known. This uncertainty presents a challenge to statisticians, who are …
Prediction and causality are of significant importance in public health and epidemiology. Questions of interest related to predictive modeling include the screening for high risk …
Individual-Level Data (IPD) approach has become increasingly popular as it does not depend on published results. Combining IPD across multiple studies usually adopts a multilevel …
We present an analysis of hospitalization rates following opioid and non-pharmacologic treatment among Medicare beneficiaries suffering from chronic back pain. Treatment for chronic back pain …
The gold standard to estimate the causal effect of an exposure on an outcome is a completely randomized design. Randomized designs are attractive for estimating …
This dissertation addresses causal inference problems when information is available from diverse sources of data. In Chapter 1 we propose methods for estimating subgroup effects …
Causal mediation analysis is widely applied in the social, economic and biological sciences to assess the causal mechanism between three variables: a treatment, an intermediate …
In South Africa, the epicentre of the HIV pandemic, there is a high prevalence of circular migration: within-country rural-to-urban cyclical movement, an artifact of apartheid-era …
Difference-in-differences (DiD) approach is one of the most popular causal inference approaches to policy effect evaluation. Employing the counterfactual parallel trends assumption, DiD can provide …
Background. Ukraine has one of the highest burdens of rifampicin-resistant tuberculosis (RR-TB) in the world, and since 2014, the country has been involved in an …
In this dissertation I examine the effects that a poverty-alleviating cash transfer administered in Pakistan for the past ten years, the Benazir Income Support Program …
This dissertation consists of various essays in econometric theory. The main part is devoted to topics at the intersection of causal inference and networks, two …
This dissertation contains four contributions to nonparametric econometrics in three chapters. The first and main chapter introduces two results for instrumental variable models with a …
There exist many non-oral treatments for osteoporosis such as teriparatide and denosumab. The purpose of this study is to evaluate the causal effect of teriparatide …
