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Modified-Half-Normal Distribution And Different Methods To Estimate Average Treatment Effect., Jingchao Sun
Modified-Half-Normal Distribution And Different Methods To Estimate Average Treatment Effect., Jingchao Sun
Electronic Theses and Dissertations
This dissertation consists of three projects related to Modified-Half-Normal distribution and causal inference. In my first project, a new distribution called Modified-Half-Normal distribution was introduced. I explored a few of its distributional properties, the procedures for generating random samples based on Bayesian approaches, and the parameter estimation based on the method of moments. The second project deals with the problem of selection bias of average treatment effect (ATE) if we use the observational data. I combined the propensity score based inverse probability of treatment weighting (IPTW) method and the directed acyclic graph (DAG) to solve this problem. The third project …
Aspects Of Causal Inference., John A. Craycroft
Aspects Of Causal Inference., John A. Craycroft
Electronic Theses and Dissertations
Observational studies differ from experimental studies in that assignment of subjects to treatments is not randomized but rather occurs due to natural mechanisms, which are usually hidden from researchers. Yet objectives of the two studies are frequently the same: identify the causal – rather than merely associational – relationship between some treatment or exposure and an outcome. The statistical issues that arise in properly analyzing observational data for this goal are numerous and fascinating, and these issues are encompassed in the domain of causal inference. The research presented in this dissertation explores several distinct aspects of causal inference. This dissertation …
Causal Effect Random Forest Of Interaction Trees For Learning Individualized Treatment Regimes In Observational Studies: With Applications To Education Study Data, Luo Li
CGU Theses & Dissertations
Learning individualized treatment regimes (ITR) using observational data holds great interest in various fields, as treatment recommendations based on individual characteristics may improve individual treatment benefits with a reduced cost. It has long been observed that different individuals may respond to a certain treatment with significant heterogeneity. ITR can be defined as a mapping between individual characteristics to a treatment assignment. The optimal ITR is the treatment assignment that maximizes expected individual treatment effects. Rooted from personalized medicine, many studies and applications of ITR are in medical fields and clinical practice. Heterogeneous responses are also well documented in educational interventions. …