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Showing 1 to 15 of 24 results Save | Export
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Peter Z. Schochet – Journal of Educational and Behavioral Statistics, 2025
Random encouragement designs evaluate treatments that aim to increase participation in a program or activity. These randomized controlled trials (RCTs) can also assess the mediated effects of participation itself on longer term outcomes using a complier average causal effect (CACE) estimation framework. This article considers power analysis…
Descriptors: Statistical Analysis, Computation, Causal Models, Research Design
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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
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Brown, Seth; Song, Mengli; Cook, Thomas D.; Garet, Michael S. – American Educational Research Journal, 2023
This study examined bias reduction in the eight nonequivalent comparison group designs (NECGDs) that result from combining (a) choice of a local versus non-local comparison group, and analytic use or not of (b) a pretest measure of the study outcome and (c) a rich set of other covariates. Bias was estimated as the difference in causal estimate…
Descriptors: Research Design, Pretests Posttests, Computation, Bias
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Li, Wei; Konstantopoulos, Spyros – Educational and Psychological Measurement, 2023
Cluster randomized control trials often incorporate a longitudinal component where, for example, students are followed over time and student outcomes are measured repeatedly. Besides examining how intervention effects induce changes in outcomes, researchers are sometimes also interested in exploring whether intervention effects on outcomes are…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Longitudinal Studies, Hierarchical Linear Modeling
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Xinxin Sun – Grantee Submission, 2023
Noncompliance to treatment assignment is widespread in randomized trials and presents challenges in causal inference. In the presence of noncompliance, the most commonly estimated effect of treatment assignment, also known as the intent-to-treat (ITT) effect, is biased. Of interest in this setting is the complier average causal effect (CACE), the…
Descriptors: Compliance (Psychology), Randomized Controlled Trials, Maximum Likelihood Statistics, Computation
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Simpson, Adrian – Journal of Research on Educational Effectiveness, 2023
Evidence-based education aims to support policy makers choosing between potential interventions. This rarely involves considering each in isolation; instead, sets of evidence regarding many potential policy interventions are considered. Filtering a set on any quantity measured with error risks the "winner's curse": conditional on…
Descriptors: Effect Size, Educational Research, Evidence Based Practice, Foreign Countries
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Dong, Nianbo; Kelcey, Benjamin; Spybrook, Jessaca – Journal of Experimental Education, 2018
Researchers are often interested in whether the effects of an intervention differ conditional on individual- or group-moderator variables such as children's characteristics (e.g., gender), teacher's background (e.g., years of teaching), and school's characteristics (e.g., urbanity); that is, the researchers seek to examine for whom and under what…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Intervention, Effect Size
Yoon, HyeonJin – ProQuest LLC, 2018
In basic regression discontinuity (RD) designs, causal inference is limited to the local area near a single cutoff. To strengthen the generality of the RD treatment estimate, a design with multiple cutoffs along the assignment variable continuum can be applied. The availability of multiple cutoffs allows estimation of a pooled average treatment…
Descriptors: Regression (Statistics), Program Evaluation, Computation, Statistical Analysis
Yoon, HyeonJin – Grantee Submission, 2018
In basic regression discontinuity (RD) designs, causal inference is limited to the local area near a single cutoff. To strengthen the generality of the RD treatment estimate, a design with multiple cutoffs along the assignment variable continuum can be applied. The availability of multiple cutoffs allows estimation of a pooled average treatment…
Descriptors: Regression (Statistics), Program Evaluation, Computation, Statistical Analysis
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Zhao, Siyuan; Heffernan, Neil – International Educational Data Mining Society, 2017
Personalized learning considers that the causal effects of a studied learning intervention may differ for the individual student. Making the inference about causal effects of studies interventions is a central problem. In this paper we propose the Residual Counterfactual Networks (RCN) for answering counterfactual inference questions, such as…
Descriptors: Computation, Outcomes of Treatment, Networks, Randomized Controlled Trials
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What Works Clearinghouse, 2020
The What Works Clearinghouse (WWC) is an initiative of the U.S. Department of Education's Institute of Education Sciences (IES), which was established under the Education Sciences Reform Act of 2002. It is an important part of IES's strategy to use rigorous and relevant research, evaluation, and statistics to improve the nation's education system.…
Descriptors: Educational Research, Evaluation Methods, Evidence, Statistical Significance
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Talloen, Wouter; Moerkerke, Beatrijs; Loeys, Tom; De Naeghel, Jessie; Van Keer, Hilde; Vansteelandt, Stijn – Journal of Educational and Behavioral Statistics, 2016
To assess the direct and indirect effect of an intervention, multilevel 2-1-1 studies with intervention randomized at the upper (class) level and mediator and outcome measured at the lower (student) level are frequently used in educational research. In such studies, the mediation process may flow through the student-level mediator (the within…
Descriptors: Intervention, Hierarchical Linear Modeling, Computation, Randomized Controlled Trials
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Kelcey, Ben – Society for Research on Educational Effectiveness, 2014
A common design in education research for interventions operating at a group or cluster level is a cluster randomized trial (CRT) (Bloom, 2005). In CRTs, intact clusters (e.g., schools) are assigned to treatment conditions rather than individuals (e.g., students) and are frequently an effective way to study interventions because they permit…
Descriptors: Cluster Grouping, Randomized Controlled Trials, Statistical Analysis, Computation
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What Works Clearinghouse, 2017
The What Works Clearinghouse (WWC) systematic review process is the basis of many of its products, enabling the WWC to use consistent, objective, and transparent standards and procedures in its reviews, while also ensuring comprehensive coverage of the relevant literature. The WWC systematic review process consists of five steps: (1) Developing…
Descriptors: Educational Research, Evaluation Methods, Evidence, Statistical Significance
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Schochet, Peter Z. – National Center for Education Evaluation and Regional Assistance, 2017
Design-based methods have recently been developed as a way to analyze data from impact evaluations of interventions, programs, and policies. The impact estimators are derived using the building blocks of experimental designs with minimal assumptions, and have good statistical properties. The methods apply to randomized controlled trials (RCTs) and…
Descriptors: Design, Randomized Controlled Trials, Quasiexperimental Design, Research Methodology
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