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The Analysis of Randomized Experiments with Missing Data

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Author Info
Pizer, William () (Resources for the Future)
Imbens, Guido

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Abstract

The otherwise straightforward analysis of randomized experiments is often complicated by the presence of missing data. In such situations it is necessary to make assumptions about the dependence of the selection mechanism on treatment, response, and covariates. The widely used approach of assuming that the data is missing at random conditional on treatment and other fully observed covariates is shown to be inadequate to describe data from a randomized experiment when partially observed covariates are also present. This paper presents an alternative to the missing at random model (MAR) which is both consistent with the data and preserves the appeal of MAR. In particular, the proposed family of models minimize the discrepancy with MAR while explaining observed deviations. We apply this approach to data from the Restart job training program in the United Kingdom as well as an artificial data set. Evaluation of the Restart program is not affected by the assumption of MAR; both approaches suggest that the program increased the chances of exiting unemployment by around 9% within six months. However, analysis of the artificial data demonstrates that assuming MAR can easily lead to erroneous conclusions.

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Paper provided by Resources For the Future in its series Discussion Papers with number dp-00-19.

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Date of creation: 01 May 2000
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Handle: RePEc:rff:dpaper:dp-00-19

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Dolton, Peter & O'Neill, Donal, 1996. "Unemployment Duration and the Restart Effect: Some Experimental Evidence," Economic Journal, Royal Economic Society, vol. 106(435), pages 387-400, March. [Downloadable!] (restricted)
  2. repec:att:wimass:199217 is not listed on IDEAS
  3. Guido W. Imbens & Donald B. Rubin & Bruce Sacerdote, 1999. "Estimating the Effects of Unearned Income on Labor Supply, Earnings, Savings, and Consumption: Evidence from a Survey of Lottery Players," NBER Working Papers 7001, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  4. Gourieroux, Christian & Monfort, Alain, 1981. "On the Problem of Missing Data in Linear Models," Review of Economic Studies, Blackwell Publishing, vol. 48(4), pages 579-86, October. [Downloadable!] (restricted)
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  1. Molinari, Francesca, 2005. "Missing Treatments," Working Papers 05-11, Cornell University, Center for Analytic Economics. [Downloadable!]
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