A variance estimator for systematic sampling from a deliberately ordered population

Berger, Yves G. (2005) A variance estimator for systematic sampling from a deliberately ordered population. Communications in Statistics: Theory and Methods, 34, (7), 1533-1541. (doi:10.1081/STA-200063383).


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Original Publication URL: http://dx.doi.org/10.1081/STA-200063383


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
Digital Object Identifier (DOI): doi:10.1081/STA-200063383
ISSNs: 0361-0926 (print)
Related URLs:
Keywords: inclusion probabilities, ?-estimator, unequal probability sampling, weighted least squares
Subjects: H Social Sciences > HA Statistics
Divisions : University Structure - Pre August 2011 > School of Social Sciences > Social Statistics
ePrint ID: 34127
Accepted Date and Publication Date:
Date Deposited: 16 May 2006
Last Modified: 31 Mar 2016 12:01
URI: http://eprints.soton.ac.uk/id/eprint/34127

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