Education Commons^™

Estimation Of Treatment Effects With Multilevel Observational Data Using Deep Neural Networks, Logistic Regression, And Multilevel Modeling: A Propensity Score Approach, Neba Nfonsang

Electronic Theses and Dissertations

This study used a propensity score approach to estimate treatment effects in a multilevel setting. The propensity score approach involves the estimation of propensity scores for covariate balancing and the estimation of treatment effects. This study aimed at understanding how propensity scores estimated through a simple logistic regression compare with propensity scores estimated through an optimized deep neural networks model. The study also examined how treatment effects estimated with propensity score weights from logistic regression compare with treatment effects estimated with propensity score weights from deep neural networks.

Few causal studies have been conducted in a multi-level setting with observational …