Ji Seung Yang

The purpose of this project was to develop a better way to deal with measurement error in predictors and to address the impact of non-normality in latent variable distributions. Predictors that contain measurement error yield attenuated correlation or regression coefficient estimates, which results in bias in treatment effect estimates. This problem is exacerbated in multilevel models when level-1 values are simply aggregated to an upper level as group means. By introducing a multilevel and ...

A regression discontinuity (RD) design is often employed to provide causal evidence when a randomized control trial is practically infeasible or unethical. Conventional RD models assume that all running variables, covariates, and outcomes are observed variables. The purpose of this grant is to extend the modeling framework to augment the structural RD model with multilevel latent variable measurement models for any or all of the variables.