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Design-based "Optimal" Calibration Weights Under Unit Nonresponse in Survey Sampling
Stockholm University, Faculty of Social Sciences, Department of Statistics.
2018 (English)Report (Other academic)
Abstract [en]

High nonresponse is a very common problem in sample surveys today. In statistical terms we are worried about increased bias and variance of estimators for population quantities such as totals or means. Different methods have been suggested in order to compensate for this phenomenon. We can roughly divide them into imputation and calibration and it is the latter approach we will focus on here. A wide spectrum of possibilities is included in the class of calibration estimators. We explore linear calibration, where we suggest using a nonresponse version of the design-based optimal regression estimator. Comparisons are made between this estimator and a GREG type estimator. Distance measures play a very important part in the construction of calibration estimators. We show that an estimator of the average response propensity (probability) can be included in the "optimal" distance measure under nonresponse, which will help reducing the bias of the resulting estimator.  To illustrate empirically the theoretically derived results for the suggested estimators, a simulation study has been carried out. The population is called KYBOK and consists of clerical municipalities in Sweden, where the variables include financial as well as size measurements. The  results are encouraging for the "optimal" estimator in combination with the estimated average response propensity, where the bias was highly reduced for the Poisson sampling cases in the study. 

Place, publisher, year, edition, pages
2018. , p. 12
Series
Research Report / Department of Statistics, Stockholm University, ISSN 0280-7564 ; 2018:2
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:su:diva-155761OAI: oai:DiVA.org:su-155761DiVA, id: diva2:1201964
Available from: 2018-04-27 Created: 2018-04-27 Last updated: 2018-04-27

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • sv-SE
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Output format
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