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Comments on the paper “Bias-adjustment and calibration of jackknife variance estimator in the presence of non-response”
Authors:Wesley Yung  David Haziza
Affiliation:1. Business Survey Methods Division, Statistics Canada, Ottawa, Ontario, Canada K1A 0T6;2. Département de mathématiques et de statistique, Université de Montréal, Montréal, Québec, Canada H3C 3J7
Abstract:Singh and Arnab (2010) presented a bias adjustment to the jackknife variance estimator of Rao and Sitter (1995) in the presence of non-response. In their paper, they obtained a second-order approximation of the bias of the Rao-Sitter variance estimator and then proposed a bias-adjusted estimator based on this approximation. To compare their proposed variance estimator to various other variance estimators, they performed a simulation study and showed that their variance estimator is superior to the Rao-Sitter variance estimator. In fact they showed that the Rao-Sitter variance estimator suffers from severe underestimation. These results contradict those in the literature, which indicate that the Rao-Sitter variance estimator suffers from a positive bias if the sampling fractions are not negligible; see Rao and Sitter (1995), Lee et al. (1995) and Haziza and Picard (2011). Because of this contradiction, we felt that a further investigation was warranted. In this paper, we attempt to recreate the results of Singh and Arnab (2010) and, in fact, show that their second order approximation to the bias of the Rao-Sitter variance estimator is incorrect and that their simulation results are also questionable.
Keywords:Bias-adjusted estimator   Jackknife variance estimation   Nonresponse   Two-phase sampling
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