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  • Publication
    Métadonnées seulement
    Calibrated random imputation for qualitative data
    In official statistics, when a file of microdata must be delivered to external users, it is very difficult to propose them a file where missing values has been treated by multiple imputations. In order to overcome this difficulty, we propose a method of single imputation for qualitative data that respect numerous constraints. The imputation is balanced on totals previously estimated; editing rules can be respected; the imputation is random, but the totals are not affected by an imputation variance.
  • Publication
    Métadonnées seulement
    A variant of the Cox algorithm for the imputation of non-response of qualitative data
    The Coxalgorithm allows to round randomly and unbiasedly a table of real numbers without modifying the marginal totals. One possible use of this method is the random imputation of aqualitative variable in survey sampling. A modification of the Coxalgorithm is proposed in order to take into account a weighting system, which is commonly used in survey sampling. The use of this new method allows to construct a controlled imputation method that reduces the imputation variance.