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Favre, Anne-Catherine
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Favre, Anne-Catherine
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Voici les éléments 1 - 7 sur 7
- PublicationMétadonnées seulementCalibrated random imputation for qualitative data(2005-3-23)
; ; 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. - PublicationMétadonnées seulement
- PublicationMétadonnées seulementA variant of the Cox algorithm for the imputation of non-response of qualitative data(2004-3-23)
; ; 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. - PublicationMétadonnées seulement
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- PublicationAccès libreOptimal allocation in balanced samplingThe development of new sampling methods allows the selection of large balanced samples. In this paper we propose a method for computing optimal inclusion probabilities for balanced samples. Next, we show that the optimal Neyman allocation is a particular case of this method.