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Joshua B. Gilbert; Luke W. Miratrix; Mridul Joshi; Benjamin W. Domingue – Journal of Educational and Behavioral Statistics, 2025
Analyzing heterogeneous treatment effects (HTEs) plays a crucial role in understanding the impacts of educational interventions. A standard practice for HTE analysis is to examine interactions between treatment status and preintervention participant characteristics, such as pretest scores, to identify how different groups respond to treatment.…
Descriptors: Causal Models, Item Response Theory, Statistical Inference, Psychometrics
Joshua B. Gilbert; Luke W. Miratrix; Mridul Joshi; Benjamin W. Domingue – Annenberg Institute for School Reform at Brown University, 2024
Analyzing heterogeneous treatment effects (HTE) plays a crucial role in understanding the impacts of educational interventions. A standard practice for HTE analysis is to examine interactions between treatment status and pre-intervention participant characteristics, such as pretest scores, to identify how different groups respond to treatment.…
Descriptors: Causal Models, Item Response Theory, Statistical Inference, Psychometrics
Lo-Hua Yuan; Avi Feller; Luke W. Miratrix – Grantee Submission, 2019
Randomized trials are often conducted with separate randomizations across multiple sites such as schools, voting districts, or hospitals. These sites can differ in important ways, including the site's implementation, local conditions, and the composition of individuals. An important question in practice is whether--and under what…
Descriptors: Causal Models, Intervention, High School Students, College Attendance

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