Title: Attrition in Randomized Control Trials: Using Tracking Information to Correct Bias
Abstract: Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL Attrition in Randomized Control Trials: Using Tracking Information to Correct Bias 85 Pages Posted: 1 May 2017 See all articles by Teresa Molina MillánTeresa Molina MillánNew University of Lisbon - Nova School of Business and EconomicsKaren MacoursParis School of Economics (PSE) There are 2 versions of this paper Attrition in Randomized Control Trials: Using Tracking Information to Correct Bias Number of pages: 85 Posted: 01 May 2017 You are currently viewing this paper Downloads 80 Attrition in Randomized Control Trials: Using Tracking Information to Correct Bias Number of pages: 90 Posted: 21 Apr 2017 Abstract This paper starts from a review of RCT studies in development economics, and documents many studies largely ignore attrition once attrition rates are found balanced between treatment arms. The paper analyzes the implications of attrition for the internal and external validity of the results of a randomized experiment with balanced attrition rates, and proposes a new method to correct for attrition bias. We rely on a 10-years longitudinal data set with a final attrition rate of 10 percent, obtained after intensive tracking of migrants, and document the sensitivity of ITT estimates for schooling gains and labour market outcomes for a social program in Nicaragua. We find that not including those found during the intensive tracking leads to an overestimate of the ITT effects for the target population by more than 35 percent, and that selection into attrition is driven by observable baseline characteristics. We propose to correct for attrition using inverse probability weighting with estimates of weights that exploit the similarities between missing individuals and those found during an intensive tracking phase. We compare these estimates with alternative strategies using regression adjustment, standard weights, bounds or proxy information. Keywords: survey non response, sample selectivity, randomized controlled trial, inverse probability weights JEL Classification: O1, C93, C52 Suggested Citation: Suggested Citation Molina Millán, Teresa and Macours, Karen, Attrition in Randomized Control Trials: Using Tracking Information to Correct Bias. Available at SSRN: https://ssrn.com/abstract=2960520 Teresa Molina Millán (Contact Author) New University of Lisbon - Nova School of Business and Economics ( email ) Campus de CampolideLisbon, 1099-032Portugal Karen Macours Paris School of Economics (PSE) ( email ) 48 Boulevard JourdanParis, 75014 75014France Download This Paper Open PDF in Browser Do you have a job opening that you would like to promote on SSRN? 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