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Quantifying ‘promising trials bias’ in randomized controlled trials in education

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posted on 2022-05-19, 14:32 authored by Sam Sims, Jake Anders, Matthew InglisMatthew Inglis, Hugues Lortie-ForguesHugues Lortie-Forgues

Randomized controlled trials have proliferated in education, in part because they provide an unbiased estimator for the causal impact of interventions. It is increasingly recognized that many such trials in education have low power to detect an effect, if indeed there is one. However, it is less well known that low powered trials tend to systematically exaggerate effect sizes among the subset of interventions that show promising results. We conduct a retrospective design analysis to quantify this bias across 23 promising trials, finding that the estimated effect sizes are exaggerated by an average of 52% or more. Promising trials bias can be reduced ex-ante by increasing the power of the trials that are commissioned and guarded against ex-post by including estimates of the exaggeration ratio when reporting trial findings. Our result also suggest that challenges around implementation fidelity are not the only reason that apparently successful interventions often fail to subsequently scale up. Instead, the findings from the initial promising trial may simply have been exaggerated.

History

School

  • Science

Department

  • Mathematics Education Centre

Published in

EdArXiv

Publisher

EdArXiv

Version

  • AO (Author's Original)

Rights holder

© The Authors

Publication date

2020-11-13

Copyright date

2020

Language

  • en

Depositor

Prof Matthew Inglis. Deposit date: 17 May 2022

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