This study proposes a two-stage causal modeling with instrumental variables to mitigate selection bias, provide correct standard error estimates, and address nonnormal and missing data issues simultaneously. Bayesian methods are used for model estimation. Robust methods with Student's "t" distributions are used to account for nonnormal…

An approach to handle partial compliance behavior using principal stratification is presented and applied to a subset of the longitudinal data from the New York City School Choice Scholarship Program, a randomized experiment designed to assess the effects of private schools versus public schools on academic achievement. The initial analysis…