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IES Grant
| Title: | Deriving and Developing Tools to Estimate Optimal Data Points for Quasi-Experimental Designs | ||
| Center: | NCER | Year: | 2020 |
| Principal Investigator: | Hedberg, Eric | Awardee: | Abt Associates, Inc. |
| Program: | Statistical and Research Methodology in Education [Program Details] | ||
| Award Period: | 3 years (07/01/2020 – 06/30/2023) | Award Amount: | $648,791 |
| Type: | Methodological Innovation | Award Number: | R305D200045 |
| Description: | Previous Award Number: R305D200023 Co-Principal Investigator: Hedges, Larry Purpose: Education policies and interventions are often implemented in ways that do not render it feasible to use a randomized control trial to test their effects. The purposes of this study are to derive theory for computing exact statistical power for three common quasi-experimental designs (QEDs) — nonequivalent control group designs, difference-in-differences, and interrupted time series — and to develop software for computing statistical power using the derived approaches for those QEDs. Project Activities: The software will be programmed in R and will thus be freely available to applied researchers. In addition to publishing in journals and presenting at conferences, the research team will use social media, press releases through NORC, briefs for nontechnical publications, and workshops at conferences, such as AERA and SREE, for applied education researchers. Products and Publications Hedberg, E. C. (2023). How Many Cases per Cluster? Operationalizing the Number of Units per Cluster Relative to Minimum Detectable Effects in Two-Level Cluster Randomized Evaluations with Linear Outcomes. American Journal of Evaluation, 44(1), 153–168. |
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