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Asymdystopia: The Threat of Small Biases in Evaluations of Education Interventions That Need to Be Powered to Detect Small Impacts
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Deke, John; Wei, Thomas; Kautz, Tim – Journal of Research on Educational Effectiveness, 2021
Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts may…
Descriptors: Intervention, Program Evaluation, Sample Size, Randomized Controlled Trials
Asymdystopia: The Threat of Small Biases in Evaluations of Education Interventions That Need to Be Powered to Detect Small Impacts
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Deke, John; Wei, Thomas; Kautz, Tim – Society for Research on Educational Effectiveness, 2018
Evaluators of education interventions increasingly need to design studies to detect impacts much smaller than the 0.20 standard deviations that Cohen (1988) characterized as "small." For example, an evaluation of Response to Intervention from the Institute of Education Sciences (IES) detected impacts ranging from 0.13 to 0.17 standard…
Descriptors: Intervention, Program Evaluation, Sample Size, Randomized Controlled Trials
Asymdystopia: The Threat of Small Biases in Evaluations of Education Interventions That Need to Be Powered to Detect Small Impacts. NCEE 2018-4002
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Deke, John; Wei, Thomas; Kautz, Tim – National Center for Education Evaluation and Regional Assistance, 2017
Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen (1988) characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts…
Descriptors: Intervention, Educational Research, Research Problems, Statistical Bias