NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Helfrich, Sara R.; Clark, Sarah K. – Reading Psychology, 2016
This study investigated differences in self-efficacy to teach literacy between two groups of pre-service teachers. The authors hypothesized that pre-service teachers enrolled in one program focusing on fewer grade levels (K-3) and requiring more literacy-focused courses would have higher self-efficacy than pre-service teachers enrolled in another…
Descriptors: Comparative Analysis, Preservice Teachers, Self Efficacy, Literacy Education
Peer reviewed Peer reviewed
Direct linkDirect link
Hong, Guanglei – Journal of Educational and Behavioral Statistics, 2010
Defining causal effects as comparisons between marginal population means, this article introduces marginal mean weighting through stratification (MMW-S) to adjust for selection bias in multilevel educational data. The article formally shows the inherent connections among the MMW-S method, propensity score stratification, and…
Descriptors: Statistical Analysis, Scores, Statistical Inference, Homogeneous Grouping