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Missing, presumed different: Quantifying the risk of attrition bias in education evaluations

Ben Weidmann and Luke Miratrix

Journal of the Royal Statistical Society Series A, 2021, vol. 184, issue 2, 732-760

Abstract: We estimate the magnitude of attrition bias for 10 randomized controlled trials (RCTs) in education. We make use of a unique feature of administrative school data in England that allows us to analyse post‐test academic outcomes for nearly all students, including those who originally dropped out of the RCTs we analyse. We find that the typical magnitude of attrition bias is 0.015 effect size units (ES), with no estimate greater than 0.034 ES. This suggests that, in practice, the risk of attrition bias is limited. However, this risk should not be ignored as we find some evidence against the common ‘Missing At Random’ assumption. Attrition appears to be more problematic for treated units. We recommend that researchers incorporate uncertainty due to attrition bias, as well as performing sensitivity analyses based on the types of attrition mechanisms that are observed in practice.

Date: 2021
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