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Peer reviewedKenneth A. Frank – Grantee Submission, 2025
Most randomized field experiments experience some attrition. Moreover, the extent of attrition may differ by treatment condition in systematic, non-random ways, biasing estimates of treatment effects and contributing to invalid inferences. We address concerns about non-random attrition by quantifying the conditions necessary in the attritted data…
Descriptors: Attrition (Research Studies), Randomized Controlled Trials, Inferences, Correlation
Ryan J. Martin; Suzannah Iadarola; Rose Iovannone; Brenna Cavanaugh; Krystal Fontechia; Lynne Levato; Cynthia M. Anderson – Journal of Developmental and Physical Disabilities, 2024
Implementation of evidence-based practices for autistic students must be informed by robust research literature. Randomized-controlled trials (RCTs) are often considered a "gold standard" methodology for determining the effectiveness of interventions. However, the complex nature of schools presents challenges for implementing successful…
Descriptors: Autism Spectrum Disorders, Students with Disabilities, Intervention, Randomized Controlled Trials
Yuan Tian; Xi Yang; Suhail A. Doi; Luis Furuya-Kanamori; Lifeng Lin; Joey S. W. Kwong; Chang Xu – Research Synthesis Methods, 2024
RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two…
Descriptors: Risk, Randomized Controlled Trials, Classification, Robotics
Miriam Hattle; Joie Ensor; Katie Scandrett; Marienke van Middelkoop; Danielle A. van der Windt; Melanie A. Holden; Richard D. Riley – Research Synthesis Methods, 2024
Individual participant data (IPD) meta-analysis projects obtain, harmonise, and synthesise original data from multiple studies. Many IPD meta-analyses of randomised trials are initiated to identify treatment effect modifiers at the individual level, thus requiring statistical modelling of interactions between treatment effect and participant-level…
Descriptors: Meta Analysis, Randomized Controlled Trials, Outcomes of Treatment, Evaluation Methods
Peter Schochet – Society for Research on Educational Effectiveness, 2024
Random encouragement designs are randomized controlled trials (RCTs) that test interventions aimed at increasing participation in a program or activity whose take up is not universal. In these RCTs, instead of randomizing individuals or clusters directly into treatment and control groups to participate in a program or activity, the randomization…
Descriptors: Statistical Analysis, Computation, Causal Models, Research Design
Huey T. Chen; Liliana Morosanu; Victor H. Chen – Asia Pacific Journal of Education, 2024
The Campbellian validity typology has been used as a foundation for outcome evaluation and for developing evidence-based interventions for decades. As such, randomized control trials were preferred for outcome evaluation. However, some evaluators disagree with the validity typology's argument that randomized controlled trials as the best design…
Descriptors: Evaluation Methods, Systems Approach, Intervention, Evidence Based Practice
Juan David Parra; D. Brent Edwards Jr. – Critical Studies in Education, 2024
This paper seeks to raise awareness among educational researchers and practitioners of some significant weaknesses and internal contradictions of randomised control trials (RCTs). Although critiques throughout the years from education scholars have pointed to the detrimental effects of this experimental approach on education practice and values,…
Descriptors: Randomized Controlled Trials, Evidence Based Practice, Educational Practices, Educational Policy
Peer reviewedKenneth A. Frank; Qinyun Lin; Spiro J. Maroulis – Grantee Submission, 2024
In the complex world of educational policy, causal inferences will be debated. As we review non-experimental designs in educational policy, we focus on how to clarify and focus the terms of debate. We begin by presenting the potential outcomes/counterfactual framework and then describe approximations to the counterfactual generated from the…
Descriptors: Causal Models, Statistical Inference, Observation, Educational Policy

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