00000nam 2200000za 4500 9.841601 CaOODSP 20221107152128 cr ||||||||||| 170814s2001 onc |o f|0| 0 eng d CaOODSP eng eng fre n-cn--- CS11-619/2001-2E-PDF Beaumont, Jean-François. On the treatment of influential observations in household surveys [electronic resource] / Jean-François Beaumont and Asma Alavi. [Ottawa] : Statistics Canada, 2001. 28 p. Working paper ; 2001-2 Digitized edition from print [produced by Statistics Canada]. "HSMD-2001-002E." "January 2001." Includes bibliographic references. "Household expenditure or income surveys often deal with highly skewed distributions, which potentially lead to samples with some extreme observations. The problem is aggravated by the fact that there usually is a low amount of useful auxiliary information available at the design stage and that the sampling design is complex most of the time, leading to widely dispersed design weights. Therefore, it could happen that a large value be associated with a large design weight and that this combination have a great influence on the estimates produced by the survey. Design consistent estimators, such as the Generalized REGression (GREG) estimator, are usually highly variable in the presence of influential observations but they have a low bias whereas model-based estimators are more stable but they are generally not consistent and more biased. In this paper, a compromise between these two types of estimators is proposed and a simulation study shows that it performs well with respect to the bias and mean squared error (MSE) criteria in comparison with some other robust estimators. Conditions under which the compromise should have a small design bias are also given"--Abstract. Abstract also in French. gccst Methodology gccst Statistical analysis gccst Surveys Alavi, Asma. Canada. Statistics Canada. Methodology Branch. Working paper (Statistics Canada. Methodology Branch) 2001-2 (CaOODSP)9.834763 PDF 3.29 MB https://publications.gc.ca/collections/collection_2017/statcan/11-613/CS11-619-2001-2-eng.pdf 11-619E no. 2001-02