relation: https://publications.ut-capitole.fr/id/eprint/25660/ title: Doubly Robust Inference for the Distribution Function in the Presence of Missing Survey Data creator: Boistard, Hélène creator: Chauvet, Guillaume creator: Haziza, David subject: B- ECONOMIE ET FINANCE description: Item non-response in surveys occurs when some, but not all, variables are missing. Unadjusted estimators tend to exhibit some bias, called the non-response bias, if the respondents differ from the non-respondents with respect to the study variables. In this paper, we focus on item non-response, which is usually treated by some form of single imputation. We examine the properties of doubly robust imputation procedures, which are those that lead to an estimator that remains consistent if either the outcome variable or the non-response mechanism is adequately modelled. We establish the double robustness property of the imputed estimator of the finite population distribution function under random hot-deck imputation within classes. We also discuss the links between our approach and that of Chambers and Dunstan. The results of a simulation study support our findings. publisher: Willey-Blackwell date: 2016-09 type: Article type: PeerReviewed identifier: Boistard, Hélène , Chauvet, Guillaume and Haziza, David (2016) Doubly Robust Inference for the Distribution Function in the Presence of Missing Survey Data. Scandinavian Journal of Statistics, 43 (3). pp. 683-699. relation: http://tse-fr.eu/pub/31939 relation: 10.1111/sjos.12198 identifier: 10.1111/sjos.12198 doi: 10.1111/sjos.12198 language: en