Efficient small-domain estimation by combining information from multiple surveys through regression / Takis Merkouris.: CS11-619/2006-7E-PDF

"In this paper, we explore the possibility of enhancing the precision of domain estimators by combining comparable information collected in multiple surveys of the same population. To this end, we propose a regression method of estimation that is essentially an extended calibration procedure whereby comparable domain estimates from the various surveys are calibrated to each other. We show through analytic results and an empirical study that this method may greatly improve the precision of domain estimators for the variables that are common to these surveys, as these estimators make effective use of increased sample size for the common survey items. The proposed design-based direct estimators involve only domain-specific data on the variables of interest. This is in contrast to small-domain (mostly, small-area) indirect estimators, based on a single survey, which incorporate through modeling data that are external to the targeted small domains. The proposed approach is also highly effective in handling the closely related problem of estimation for rare population characteristics"--Abstract.

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Publication information
Department/Agency Canada. Statistics Canada. Methodology Branch. Household Survey Methods Division.
Title Efficient small-domain estimation by combining information from multiple surveys through regression / Takis Merkouris.
Series title Working paper ; 2006-7
Publication type Series - View Master Record
Language [English]
Format Electronic
Electronic document
Note(s) Digitized edition from print [produced by Statistics Canada].
"HSMD-2006-007E."
"June 2006."
Includes bibliographic references.
Abstract also in French.
Publishing information [Ottawa] : Statistics Canada, 2006.
Author / Contributor Merkouris, Takis.
Description 21 p.
Catalogue number
  • CS11-619/2006-7E-PDF
Departmental catalogue number 11-619E no. 2006-007
Subject terms Methodology
Statistical analysis
Surveys
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