Multiple imputation when records used for imputation are not used or disseminated for analysis |
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Authors: | Reiter Jerome P |
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Institution: | Department of Statistical Science, Duke University, Durham, North Carolina 27708-0251, U.S.A. jerry{at}stat.duke.edu |
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Abstract: | When some of the records used to estimate the imputation modelsin multiple imputation are not used or available for analysis,the usual multiple imputation variance estimator has positivebias. We present an alternative approach that enables unbiasedestimation of variances and, hence, calibrated inferences insuch contexts. First, using all records, the imputer samplesm values of the parameters of the imputation model. Second,for each parameter draw, the imputer simulates the missing valuesfor all records n times. From these mn completed datasets, theimputer can analyse or disseminate the appropriate subset ofrecords. We develop methods for interval estimation and significancetesting for this approach. Methods are presented in the contextof multiple imputation for measurement error. |
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Keywords: | Combining data Confidentiality Measurement error Missing data Multiple imputation |
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