References (49)


Citations (2)



Definition and Diagnosis of Problematic Attrition in Randomized Controlled Experiments

Fernando Martel García


May 26, 2013

Attrition is the Achilles' Heel of the randomized experiment: It is fairly common, and it can completely unravel the benefits of randomization. Using the structural language of causal diagrams I demonstrate that attrition is problematic for identification of the average treatment effect (ATE) if -- and only if -- it is a common effect of the treatment and the outcome (or a cause of the outcome other than the treatment). I also demonstrate that whether the ATE is identified and estimable for all units in the experiment, or only for those units with observed outcomes, depends on two d-separation conditions. One of these is testable ex-post under standard experimental assumptions. The other is testable ex-ante so long as adequate measurement protocols are adopted. Missing at Random (MAR) assumptions are neither necessary nor sufficient for identification of the ATE.

Number of Pages in PDF File: 53

Keywords: attrition, randomized controlled experiments, field experiments, causal diagrams, directed acyclic graphs, average treatment effect, nonparametric

Download This Paper

Date posted: July 30, 2013  

Suggested Citation

Martel García, Fernando, Definition and Diagnosis of Problematic Attrition in Randomized Controlled Experiments (May 26, 2013). Available at SSRN: http://ssrn.com/abstract=2302735 or http://dx.doi.org/10.2139/ssrn.2302735

Contact Information

Fernando Martel García (Contact Author)
Independent ( email )
No Address Available
United States
Feedback to SSRN

Paper statistics
Abstract Views: 374
Downloads: 77
Download Rank: 137,168
References:  49
Citations:  2

© 2015 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo2 in 0.344 seconds