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Design and Analytic Features for Reducing Biases in Skill-Building Intervention Impact Forecasts

Daniela Alvarez-Vargas, Sirui Wan, Lynn S. Fuchs, Alice Klein, & Drew H. Bailey

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Despite policy relevance, long term evaluations of educational interventions are rare relative to the amount of end of treatment evaluations. A common approach to this problem is to use statistical models to forecast the long-term effects of an intervention based on the estimated shorter term effects. Such forecasts typically rely on the correlation between children’s early skills (e.g., preschool numeracy) and medium-term outcomes (e.g., 1st grade math achievement), calculated from longitudinal data available outside the evaluation. This approach sometimes over- or under-predicts the longer-term effects of early academic interventions, raising concerns about how best to forecast the long-term effects of such interventions. The present paper provides a methodological approach to assessing the types of research design and analysis specifications that may reduce biases in such forecasts.

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Between-School Variation in Students’ Achievement, Motivation, Affect, and Learning Strategies: Results from 81 Countries for Planning Cluster-Randomized Trials in Education

Martin Brunner, Uli Keller, Marina Wenger, Antoine Fischbach & Oliver Lüdtke

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Does an educational intervention work?

When planning an evaluation, researchers should ensure that it has enough statistical power to detect the expected intervention effect. The minimally detectable effect size, or MDES, is the smallest true effect size a study is well positioned to detect. If the MDES is too large, researchers may erroneously conclude that their intervention does not work even when it does. If the MDES is too small, that is not a problem per se, but it may mean increased cost to conduct the study.  The sample size, along with several other factors, known as design parameters, go into calculating the MDES. Researchers must estimate these design parameters. This paper provides an empirical bases for estimating design parameters in 81 countries across various outcomes.

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