Domains of study and poststratification
Domains of study and poststratification
Sugden and Smith (2002. J. Statist. Plann. Inference 102, 25-38) investigated conditions under which exact linear unbiased estimators of linear estimands, and also exact quadratic unbiased estimators of quadratic estimands, could be constructed under the randomisation approach. In this paper the method is applied to domains of study and extended to poststratified estimators of finite population totals. The resulting estimators generalise some of those in Doss et al. (1979. J. Statist. Plann. Inference 3, 235-247). Some further properties of these estimators are explored.
general linear estimator, exact unbiasedness, domains of study, conditional moments, unconditional moments, large sample approximations, randomisation distribution
3307-3317
Sugden, R.A.
0483483b-5c6c-4f41-9b21-ff25a1c0e4ac
Smith, T.M.F.
61602253-c2d6-43a1-862b-291379e75318
1 September 2006
Sugden, R.A.
0483483b-5c6c-4f41-9b21-ff25a1c0e4ac
Smith, T.M.F.
61602253-c2d6-43a1-862b-291379e75318
Sugden, R.A. and Smith, T.M.F.
(2006)
Domains of study and poststratification.
Journal of Statistical Planning and Inference, 136 (9), .
(doi:10.1016/j.jspi.2004.12.010).
Abstract
Sugden and Smith (2002. J. Statist. Plann. Inference 102, 25-38) investigated conditions under which exact linear unbiased estimators of linear estimands, and also exact quadratic unbiased estimators of quadratic estimands, could be constructed under the randomisation approach. In this paper the method is applied to domains of study and extended to poststratified estimators of finite population totals. The resulting estimators generalise some of those in Doss et al. (1979. J. Statist. Plann. Inference 3, 235-247). Some further properties of these estimators are explored.
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Published date: 1 September 2006
Additional Information:
Received 6 August 2004; revised 8 December 2004; accepted 9 December 2004.
Keywords:
general linear estimator, exact unbiasedness, domains of study, conditional moments, unconditional moments, large sample approximations, randomisation distribution
Identifiers
Local EPrints ID: 48124
URI: http://eprints.soton.ac.uk/id/eprint/48124
ISSN: 0378-3758
PURE UUID: ae0830e6-19d2-4bc6-a927-07b5393e70f6
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Date deposited: 29 Aug 2007
Last modified: 15 Mar 2024 09:43
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Contributors
Author:
R.A. Sugden
Author:
T.M.F. Smith
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