Propensity score–based analysis is increasingly being used in observational studies to
estimate the effects of treatments, interventions, and exposures. We introduce the concept of …

In this study, we use double-robust estimators (ie, inverse probability weighting and inverse
probability weighting with regression adjustment) to quantify the effect of adopting climate …

Objective To compare the real‐life effectiveness of biologic therapy (a biologic disease‐
modifying antirheumatic drug plus methotrexate [MTX]) versus triple therapy (MTX plus …

Background For patients with MS, medication switches increase the risk of disease
reactivation. Objective Compare discontinuation rates due to treatment failure or side effects …

Propensity score matching is widely used to determine the effects of treatments in
observational studies. Competing risk survival data are common to medical research …

A case-control study is designed to help determine if an exposure is associated with an
outcome. However, since case-control studies are retrospective, they are often subject to …

The propensity score is the probability of receiving the treatment given a set of baseline
covariates. The two properties of the propensity score has been illustrated under the …

In this dissertation, I use novel methodologies that incorporate machine learning into causal
policy evaluation such as double robust machine learning to study some key issues in …

Economic turmoil has forced higher education institutions (HEI) to reduce expenditures in
many areas, including human resource operations such as talent development. Before …

Mood and anxiety disorders are some of the biggest contributors to morbidity worldwide, and
may be lethal. Appropriate treatment is therefore paramount. Antidepressant medications …