Variance estimation for systematic sampling from deliberately ordered populations

Full text not archived in this repository.

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

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 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.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/9491
Identification Number/DOI 10.1081/STA-200063383
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics > Applied Statistics
Uncontrolled Keywords inclusion probabilities, π-estimator, unequal probability sampling, weighted least squares
Download/View statistics View download statistics for this item

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar