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Small area estimation under transformation to linearity

Journal Article


Abstract


  • Small area estimation based on linear mixed models can be inefficient when the underlying relationships are non-linear. In

    this paper we introduce SAE techniques for variables that can be modelled linearly following a non-linear transformation. In

    particular, we extend the model-based direct estimator of Chandra and Chambers (2005, 2009) to data that are consistent

    with a linear mixed model in the logarithmic scale, using model calibration to define appropriate weights for use in this

    estimator. Our results show that the resulting transformation-based estimator is both efficient and robust with respect to the

    distribution of the random effects in the model. An application to business survey data demonstrates the satisfactory

    performance of the method.

Publication Date


  • 2011

Citation


  • Chandra, H. & Chambers, R. L. (2011). Small area estimation under transformation to linearity. Survey Methodology, 37 (1), 39-51.

Scopus Eid


  • 2-s2.0-79960258654

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/3616

Number Of Pages


  • 12

Start Page


  • 39

End Page


  • 51

Volume


  • 37

Issue


  • 1

Place Of Publication


  • http://www.statcan.gc.ca/pub/12-001-x/2011001/article/11446-eng.pdf

Abstract


  • Small area estimation based on linear mixed models can be inefficient when the underlying relationships are non-linear. In

    this paper we introduce SAE techniques for variables that can be modelled linearly following a non-linear transformation. In

    particular, we extend the model-based direct estimator of Chandra and Chambers (2005, 2009) to data that are consistent

    with a linear mixed model in the logarithmic scale, using model calibration to define appropriate weights for use in this

    estimator. Our results show that the resulting transformation-based estimator is both efficient and robust with respect to the

    distribution of the random effects in the model. An application to business survey data demonstrates the satisfactory

    performance of the method.

Publication Date


  • 2011

Citation


  • Chandra, H. & Chambers, R. L. (2011). Small area estimation under transformation to linearity. Survey Methodology, 37 (1), 39-51.

Scopus Eid


  • 2-s2.0-79960258654

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/3616

Number Of Pages


  • 12

Start Page


  • 39

End Page


  • 51

Volume


  • 37

Issue


  • 1

Place Of Publication


  • http://www.statcan.gc.ca/pub/12-001-x/2011001/article/11446-eng.pdf