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Item non-response in surveys is usually handled by single imputation, whosemain objective is to reduce the non-response bias. Imputation methods need tobe adapted to the study variable. For instance, in business surveys, theinterest variables often contain a large number of zeros. Motivated by amixture regression model, we propose two imputation procedures for such dataand study their statistical properties. We show that these procedures preservethe distribution function if the imputation model is well specified. Theresults of a simulation study illustrate the good performance of the proposedmethods in terms of bias and mean square error.

Preserving the distribution function in surveys in case of imputation for zero inflated data