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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
Raudenbush, Stephen W.; Sadoff, Sally – Journal of Research on Educational Effectiveness, 2008
A dramatic shift in research priorities has recently produced a large number of ambitious randomized trials in K-12 education. In most cases, the aim is to improve student academic learning by improving classroom instruction. Embedded in these studies are theories about how the quality of classroom must improve if these interventions are to…
Descriptors: Elementary Secondary Education, Error of Measurement, Statistical Inference, Program Evaluation