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Generalised Regression Estimation Given Imperfectly Matched Auxiliary Data

Author

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  • Zhang Li-Chun

    (University of Southampton, Social Statistics and Demography, Highfield, Southampton, SO17 1BJ, UK.)

Abstract

Generalised regression estimation allows one to make use of available auxiliary information in survey sampling. We develop three types of generalised regression estimator when the auxiliary data cannot be matched perfectly to the sample units, so that the standard estimator is inapplicable. The inference remains design-based. Consistency of the proposed estimators is either given by construction or else can be tested given the observed sample and links. Mean square errors can be estimated. A simulation study is used to explore the potentials of the proposed estimators.

Suggested Citation

  • Zhang Li-Chun, 2021. "Generalised Regression Estimation Given Imperfectly Matched Auxiliary Data," Journal of Official Statistics, Sciendo, vol. 37(1), pages 239-255, March.
    • Handle: RePEc:vrs:offsta:v:37:y:2021:i:1:p:239-255:n:4
    DOI: 10.2478/jos-2021-0010
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