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Timo Gnambs; Ulrich Schroeders – Research Synthesis Methods, 2024
Meta-analyses of treatment effects in randomized control trials are often faced with the problem of missing information required to calculate effect sizes and their sampling variances. Particularly, correlations between pre- and posttest scores are frequently not available. As an ad-hoc solution, researchers impute a constant value for the missing…
Descriptors: Accuracy, Meta Analysis, Randomized Controlled Trials, Effect Size
Lesley J. Turner; Oded Gurantz – Annenberg Institute for School Reform at Brown University, 2024
College attendance has increased significantly over the last few decades, but dropout rates remain high, with fewer than half of all adults ultimately obtaining a postsecondary credential. This project investigates whether one-on-one college coaching improves college attendance and completion outcomes for former low- and middle-income income state…
Descriptors: College Students, Coaching (Performance), Attendance, Alumni
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Nianbo Dong; Benjamin Kelcey; Jessaca Spybrook; Yanli Xie; Dung Pham; Peilin Qiu; Ning Sui – Grantee Submission, 2024
Multisite trials that randomize individuals (e.g., students) within sites (e.g., schools) or clusters (e.g., teachers/classrooms) within sites (e.g., schools) are commonly used for program evaluation because they provide opportunities to learn about treatment effects as well as their heterogeneity across sites and subgroups (defined by moderating…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Educational Research, Effect Size
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Justin Boutilier; Jonas Jonasson; Hannah Li; Erez Yoeli – Society for Research on Educational Effectiveness, 2024
Background: Randomized controlled trials (RCTs), or experiments, are the gold standard for intervention evaluation. However, the main appeal of RCTs--the clean identification of causal effects--can be compromised by interference, when one subject's actions can influence another subject's behavior or outcomes. In this paper, we formalize and study…
Descriptors: Randomized Controlled Trials, Intervention, Mathematical Models, Interference (Learning)
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Sandra Jo Wilson; Brian Freeman; E. C. Hedberg – Grantee Submission, 2024
As reporting of effect sizes in evaluation studies has proliferated, researchers and consumers of research need tools for interpreting or benchmarking the magnitude of those effect sizes that are relevant to the intervention, target population, and outcome measure being considered. Similarly, researchers planning education studies with social and…
Descriptors: Benchmarking, Effect Size, Meta Analysis, Statistical Analysis
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Edoardo G. Ostinelli; Orestis Efthimiou; Yan Luo; Clara Miguel; Eirini Karyotaki; Pim Cuijpers; Toshi A. Furukawa; Georgia Salanti; Andrea Cipriani – Research Synthesis Methods, 2024
When studies use different scales to measure continuous outcomes, standardised mean differences (SMD) are required to meta-analyse the data. However, outcomes are often reported as endpoint or change from baseline scores. Combining corresponding SMDs can be problematic and available guidance advises against this practice. We aimed to examine the…
Descriptors: Network Analysis, Meta Analysis, Depression (Psychology), Regression (Statistics)
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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
Lydia Bradford – ProQuest LLC, 2024
In randomized control trials (RCT), the recent focus has shifted to how an intervention yields positive results on its intended outcome. This aligns with the recent push of implementation science in healthcare (Bauer et al., 2015) but goes beyond this. RCTs have moved to evaluating the theoretical framing of the intervention as well as differing…
Descriptors: Hierarchical Linear Modeling, Mediation Theory, Randomized Controlled Trials, Research Design
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