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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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Direct linkKaplan, Avi; Cromley, Jennifer; Perez, Tony; Dai, Ting; Mara, Kyle; Balsai, Michael – Educational Researcher, 2020
In this commentary, we complement other constructive critiques of educational randomized control trials (RCTs) by calling attention to the commonly ignored role of context in causal mechanisms undergirding educational phenomena. We argue that evidence for the central role of context in causal mechanisms challenges the assumption that RCT findings…
Descriptors: Context Effect, Educational Research, Randomized Controlled Trials, Causal Models
Kaplan, Avi; Cromley, Jennifer; Perez, Tony; Dai, Ting; Mara, Kyle; Balsai, Michael – Grantee Submission, 2020
In this commentary, we complement other constructive critiques of educational randomized control trials (RCTs) by calling attention to the commonly ignored role of context in causal mechanisms undergirding educational phenomena. We argue that evidence for the central role of context in causal mechanisms challenges the assumption that RCT findings…
Descriptors: Context Effect, Educational Research, Randomized Controlled Trials, Causal Models
Reardon, Sean F.; Raudenbush, Stephen W. – Grantee Submission, 2013
The increasing availability of data from multi-site randomized trials provides a potential opportunity to use instrumental variables methods to study the effects of multiple hypothesized mediators of the effect of a treatment. We derive nine assumptions needed to identify the effects of multiple mediators when using site-by-treatment interactions…
Descriptors: Causal Models, Measures (Individuals), Research Design, Context Effect
Reardon, Sean F.; Raudenbush, Stephen W. – Society for Research on Educational Effectiveness, 2011
The purpose of this paper is to clarify the assumptions that must be met if this--multiple site, multiple mediator--strategy, hereafter referred to as "MSMM," is to identify the average causal effects (ATE) in the populations of interest. The authors' investigation of the assumptions of the multiple-mediator, multiple-site IV model demonstrates…
Descriptors: Educational Research, Social Science Research, Research Design, Causal Models
Cook, Thomas D.; Shadish, William R.; Wong, Vivian C. – Journal of Policy Analysis and Management, 2008
This paper analyzes 12 recent within-study comparisons contrasting causal estimates from a randomized experiment with those from an observational study sharing the same treatment group. The aim is to test whether different causal estimates result when a counterfactual group is formed, either with or without random assignment, and when statistical…
Descriptors: Causal Models, Experiments, Pretests Posttests, Job Training
Peer reviewedSheehan, Janet K.; Han, Tianqi – Mid-Western Educational Researcher, 1996
Contrasts aptitude by treatment interaction (ATI) and hierarchical linear modeling (HLM) methods for making cross-level inferences between individual-level and group-level factors in school effectiveness research. Recommends HLM when intraclass correlations are high. ATI is suitable when intraclass correlations are low, but partitioning the…
Descriptors: Aptitude Treatment Interaction, Causal Models, Context Effect, Educational Research
