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Eli Ben-Michael; Lindsay Page; Luke Keele – Grantee Submission, 2024
In a clustered observational study, a treatment is assigned to groups and all units within the group are exposed to the treatment. We develop a new method for statistical adjustment in clustered observational studies using approximate balancing weights, a generalization of inverse propensity score weights that solve a convex optimization problem…
Descriptors: Research Design, Statistical Data, Multivariate Analysis, Observation
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Ethan R. Van Norman; David A. Klingbeil; Adelle K. Sturgell – Grantee Submission, 2024
Single-case experimental designs (SCEDs) have been used with increasing frequency to identify evidence-based interventions in education. The purpose of this study was to explore how several procedural characteristics, including within-phase variability (i.e., measurement error), number of baseline observations, and number of intervention…
Descriptors: Research Design, Case Studies, Effect Size, Error of Measurement
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Ting Ye; Ted Westling; Lindsay Page; Luke Keele – Grantee Submission, 2024
The clustered observational study (COS) design is the observational study counterpart to the clustered randomized trial. In a COS, a treatment is assigned to intact groups, and all units within the group are exposed to the treatment. However, the treatment is non-randomly assigned. COSs are common in both education and health services research. In…
Descriptors: Nonparametric Statistics, Identification, Causal Models, Multivariate Analysis
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Christina Weiland; Rebecca Unterman; Susan Dynarski; Rachel Abenavoli; Howard Bloom; Breno Braga; Anne-Marie Faria; Erica Greenberg; Brian A. Jacob; Jane Arnold Lincove; Karen Manship; Meghan McCormick; Luke Miratrix; Tomás E. Monarrez; Pamela Morris-Perez; Anna Shapiro; Jon Valant; Lindsay Weixler – Grantee Submission, 2024
Lottery-based identification strategies offer potential for generating the next generation of evidence on U.S. early education programs. The authors' collaborative network of five research teams applying this design in early education settings and methods experts has identified six challenges that need to be carefully considered in this next…
Descriptors: Early Childhood Education, Program Evaluation, Evaluation Methods, Admission (School)
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Jennifer R. Morrison; Eugene Borokhovski; Robert M. Bernard; Robert E. Slavin – Grantee Submission, 2024
Research and theory indicate that the type and quality of instruction, not the delivery mechanism, are what impact learning. Previous reviews have not systematically explored variations in the instructional strategies, approaches, and designs of educational technology programs and also suffered from lax inclusion criteria, which has been known to…
Descriptors: Elementary Secondary Education, Mathematics Education, Educational Technology, Research Methodology
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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