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Variance estimation for systematic sampling from deliberately ordered populations

Berger, Y.G. (2005) Variance estimation for systematic sampling from deliberately ordered populations. Communications in Statistics - Theory and Methods, 34 (7). pp. 1533-1541. ISSN 0361-0926

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To link to this article DOI: 10.1081/STA-200063383

Abstract/Summary

The systematic sampling (SYS) design (Madow and Madow, 1944) is widely used by statistical offices due to its simplicity and efficiency (e.g., Iachan, 1982). But it suffers from a serious defect, namely, that it is impossible to unbiasedly estimate the sampling variance (Iachan, 1982) and usual variance estimators (Yates and Grundy, 1953) are inadequate and can overestimate the variance significantly (Särndal et al., 1992). We propose a novel variance estimator which is less biased and that can be implemented with any given population order. We will justify this estimator theoretically and with a Monte Carlo simulation study.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > Department of Mathematics and Statistics > Applied Statistics
ID Code:9491
Uncontrolled Keywords:inclusion probabilities, π-estimator, unequal probability sampling, weighted least squares

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