Design and Analytic Features for Reducing Biases in Skill-Building Intervention Impact Forecasts
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| Title: | Design and Analytic Features for Reducing Biases in Skill-Building Intervention Impact Forecasts |
|---|---|
| Language: | English |
| Authors: | Alvarez-Vargas, Daniela (ORCID |
| Source: | Journal of Research on Educational Effectiveness. 2023 16(2):271-299. |
| Availability: | Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Peer Reviewed: | Y |
| Page Count: | 29 |
| Publication Date: | 2023 |
| Sponsoring Agency: | Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) (DHHS/NIH) Institute of Education Sciences (ED) National Science Foundation (NSF) |
| Contract Number: | 2R01HD053714 U54HD083211 R305K050004 DGE1839285 |
| Intended Audience: | Researchers |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Early Childhood Education Elementary Education Grade 1 Primary Education |
| Descriptors: | Bias, Skill Development, Intervention, Program Evaluation, Prediction, Mathematics Skills, Regression (Statistics), Program Effectiveness, Mathematics Achievement, Outcomes of Education, Grade 1, Elementary School Students, Achievement Tests |
| Assessment and Survey Identifiers: | Wide Range Achievement Test |
| DOI: | 10.1080/19345747.2022.2093298 |
| ISSN: | 1934-5747 1934-5739 |
| Abstract: | Despite policy relevance, longer-term evaluations of educational interventions are relatively rare. A common approach to this problem has been to rely on longitudinal research to determine targets for intervention by looking at the correlation between children's early skills (e.g., preschool numeracy) and medium-term outcomes (e.g., first-grade math achievement). However, this approach has sometimes over--or under--predicted the long-term effects (e.g., 5th-grade math achievement) of successfully improving early math skills. Using a within-study comparison design, we assess various approaches to forecasting medium-term impacts of early math skill-building interventions. The most accurate forecasts were obtained when including comprehensive baseline controls and using a combination of conceptually proximal and distal short-term outcomes (in the nonexperimental longitudinal data). Researchers can use our approach to establish a set of designs and analyses to predict the impacts of their interventions up to 2 years post-treatment. The approach can also be applied to power analyses, model checking, and theory revisions to understand mechanisms contributing to medium-term outcomes. |
| Abstractor: | As Provided |
| Notes: | https://osf.io/eszau |
| IES Funded: | Yes |
| Entry Date: | 2023 |
| Accession Number: | EJ1387534 |
| Database: | ERIC |
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