Estimation multi-robuste efficace en présence de données influentes
Item nonresponse is a common issue in surveys. Because unadjusted estimators may be biased in the presence of nonresponse, it is common practice to impute the missing values, leading to the creation of a completed data file, in order to reduce the nonresponse bias. Moreover, the commonly used estimators of population totals/means are very unstable in the presence of influential units. We develop an efficient version, in the presence of influential units, of multiply robust estimators, which are estimators obtained after a multiply robust imputation method. To do so, we define the conditional bias of a sample unit as its measure of influence. We will present the results of a simulation study to show the benefits of the proposed method in terms of bias and efficiency.
Robustness Multiply robust imputation Conditional bias Design-based inference Influential units Item nonresponse