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Lyu, Weicong; Kim, Jee-Seon; Suk, Youmi – Journal of Educational and Behavioral Statistics, 2023
This article presents a latent class model for multilevel data to identify latent subgroups and estimate heterogeneous treatment effects. Unlike sequential approaches that partition data first and then estimate average treatment effects (ATEs) within classes, we employ a Bayesian procedure to jointly estimate mixing probability, selection, and…
Descriptors: Hierarchical Linear Modeling, Bayesian Statistics, Causal Models, Statistical Inference
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Bao, Lei; Koenig, Kathleen; Xiao, Yang; Fritchman, Joseph; Zhou, Shaona; Chen, Cheng – Physical Review Physics Education Research, 2022
Abilities in scientific thinking and reasoning have been emphasized as core areas of initiatives, such as the Next Generation Science Standards or the College Board Standards for College Success in Science, which focus on the skills the future will demand of today's students. Although there is rich literature on studies of how these abilities…
Descriptors: Physics, Science Instruction, Teaching Methods, Thinking Skills
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Jin, Hui; Rubin, Donald B. – Journal of Educational and Behavioral Statistics, 2009
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…
Descriptors: Statistical Inference, Causal Models, Longitudinal Studies, Public Schools