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The Census Coverage and Measurement program at the U.S. Census Bureau uses dual system estimation to measure the accuracy of the decennial census. Construction of the dual system estimator involves first estimating the percentage of correctly enumerated persons in the decennial census within different domains. This estimation is complicated by the presence of unresolved census enumerations (missing data) for which enumeration status (correct or erroneous) can not be determined. Furthermore, there is concern that the propensity to respond depends on enumeration status, that is, that the missing data are not missing at random. This paper is an exploration of different missing data models and their effect on the prediction of enumeration status, and in particular a comparison of missing at random and not missing at random data models.
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