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Title: Missing, presumed different: Quantifying the risk of attrition bias in education evaluations Authors:  Ben Weidmann - Harvard Kennedy School (United Kingdom) [presenting]
Abstract: The magnitude of attrition bias for 10 randomized controlled trials (RCTs) in education is estimated. 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 perform sensitivity analyses based on the types of attrition mechanisms that are observed in practice.