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Kenneth 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
Thoemmes, Felix; Liao, Wang; Jin, Ze – Journal of Educational and Behavioral Statistics, 2017
This article describes the analysis of regression-discontinuity designs (RDDs) using the R packages rdd, rdrobust, and rddtools. We discuss similarities and differences between these packages and provide directions on how to use them effectively. We use real data from the Carolina Abecedarian Project to show how an analysis of an RDD can be…
Descriptors: Regression (Statistics), Research Design, Robustness (Statistics), Computer Software
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Hedberg, E. C.; Hedges, L. V.; Kuyper, A. M. – Society for Research on Educational Effectiveness, 2015
Randomized experiments are generally considered to provide the strongest basis for causal inferences about cause and effect. Consequently randomized field trials have been increasingly used to evaluate the effects of education interventions, products, and services. Populations of interest in education are often hierarchically structured (such as…
Descriptors: Randomized Controlled Trials, Hierarchical Linear Modeling, Correlation, Computation
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Weiss, Michael J.; Bloom, Howard S.; Verbitsky-Savitz, Natalya; Gupta, Himani; Vigil, Alma E.; Cullinan, Daniel N. – Journal of Research on Educational Effectiveness, 2017
Multisite trials, in which individuals are randomly assigned to alternative treatment arms within sites, offer an excellent opportunity to estimate the cross-site average effect of treatment assignment (intent to treat or ITT) "and" the amount by which this impact varies across sites. Although both of these statistics are substantively…
Descriptors: Randomized Controlled Trials, Evidence, Models, Intervention
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Bloom, Howard S.; Porter, Kristin E.; Weiss, Michael J.; Raudenbush, Stephen – Society for Research on Educational Effectiveness, 2013
To date, evaluation research and policy analysis have focused mainly on average program impacts and paid little systematic attention to their variation. Recently, the growing number of multi-site randomized trials that are being planned and conducted make it increasingly feasible to study "cross-site" variation in impacts. Important…
Descriptors: Research Methodology, Policy, Evaluation Research, Randomized Controlled Trials
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Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen – American Journal of Evaluation, 2016
Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…
Descriptors: Intervention, Multivariate Analysis, Mixed Methods Research, Models