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On combining independent probability samples
SLU, Umeå.
Umeå universitet, Umeå; SLU, Umeå.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences.
Umeå universitet, Umeå.
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2019 (English)In: Survey Methodology, ISSN 0714-0045, E-ISSN 1492-0921, Vol. 45, no 2, p. 371-387Article in journal (Refereed) Published
Abstract [en]

Merging available sources of information is becoming increasingly important for improving estimates ofpopulation characteristics in a variety of fields. In presence of several independent probability samples from afinite population we investigate options for a combined estimator of the population total, based on either a linearcombination of the separate estimators or on the combined sample approach. A linear combination estimatorbased on estimated variances can be biased as the separate estimators of the population total can be highlycorrelated to their respective variance estimators. We illustrate the possibility to use the combined sample toestimate the variances of the separate estimators, which results in general pooled variance estimators. Thesepooled variance estimators use all available information and have potential to significantly reduce bias of a linearcombination of separate estimators.

Place, publisher, year, edition, pages
Statistics Canada , 2019. Vol. 45, no 2, p. 371-387
Keywords [en]
Horvitz-Thompson estimator, Inclusion probabilities, Linear combination estimator, Variance estimation
Identifiers
URN: urn:nbn:se:miun:diva-36835Scopus ID: 2-s2.0-85068768578OAI: oai:DiVA.org:miun-36835DiVA, id: diva2:1342092
Note

In French: Combinaison d’échantillons probabilistes indépendants

Available from: 2019-08-12 Created: 2019-08-12 Last updated: 2019-08-12Bibliographically approved

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Scopushttps://www150.statcan.gc.ca/n1/pub/12-001-x/2019002/article/00003-eng.htm

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Jonsson, Bengt-Gunnar

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  • apa
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