Résumé

Variance estimation in the case of item nonresponse treated by imputation is the main topic of this work. Treating the imputed values as if they were observed may lead to a substantial under-estimation of the variance of point estimators. Classical variance estimators rely on the availability of the second-order inclusion probabilities, which are difficult to calculate. We propose to study the properties of variance estimators obtained by approximating the second-order inclusion probabilities. These approximations are usually valid for high entropy sampling designs. The results of a simulation study evaluating the properties of the proposed variance estimators in terms of bias and mean squared error will be presented.

Audrey-Anne Vallée