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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
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
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
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
K. L. Anglin; A. Krishnamachari; V. Wong – Grantee Submission, 2020
This article reviews important statistical methods for estimating the impact of interventions on outcomes in education settings, particularly programs that are implemented in field, rather than laboratory, settings. We begin by describing the causal inference challenge for evaluating program effects. Then four research designs are discussed that…
Descriptors: Causal Models, Statistical Inference, Intervention, Program Evaluation
What Works Clearinghouse, 2022
Education decisionmakers need access to the best evidence about the effectiveness of education interventions, including practices, products, programs, and policies. It can be difficult, time consuming, and costly to access and draw conclusions from relevant studies about the effectiveness of interventions. The What Works Clearinghouse (WWC)…
Descriptors: Program Evaluation, Program Effectiveness, Standards, Educational Research
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
Joyce, Kathryn E.; Cartwright, Nancy – American Educational Research Journal, 2020
This article addresses the gap between what works in research and what works in practice. Currently, research in evidence-based education policy and practice focuses on randomized controlled trials. These can support causal ascriptions ("It worked") but provide little basis for local effectiveness predictions ("It will work…
Descriptors: Theory Practice Relationship, Educational Policy, Evidence Based Practice, Educational Research
Lo-Hua Yuan; Avi Feller; Luke W. Miratrix – Grantee Submission, 2019
Randomized trials are often conducted with separate randomizations across multiple sites such as schools, voting districts, or hospitals. These sites can differ in important ways, including the site's implementation, local conditions, and the composition of individuals. An important question in practice is whether--and under what…
Descriptors: Causal Models, Intervention, High School Students, College Attendance
Stephen Gorard; Beng H. See; Nadia Siddiqui – Sage Research Methods Cases, 2014
This case describes a current evaluation of an educational intervention to help disadvantaged children catch up in literacy at around the time they transfer to their senior school. The evaluation is based on a randomised controlled trial design, which the case explains is the most appropriate for testing or establishing a causal claim. The case…
Descriptors: Randomized Controlled Trials, Educational Research, Intervention, Observation