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Towards optimal regression estimation in sample surveys

Record type: Article

The Montanari (1987) regression estimator is optimal when the population regression coefficients are known. When the coefficients are estimated, the Montanari estimator is not optimal and can be extremely volatile. Using design-based arguments, this paper proposes a simpler and better alternative to the Montanari estimator that is also optimal when the population regression coefficients are known. Moreover, it can be easily implemented as it involves standard weighted least squares. The estimator is applicable under single stage stratified sampling with unequal probabilities within each stratum.

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Citation

Berger, Yves G., Tirari, Mohammed E.H. and Tille, Yves (2003) Towards optimal regression estimation in sample surveys Australian and New Zealand Journal of Statistics, 45, (3), pp. 319-329. (doi:10.1111/1467-842X.00286).

More information

Published date: 2003
Keywords: design-based inference, generalized regression estimator, inclusion probabilities, montanari estimator, conditional poisson sampling

Identifiers

Local EPrints ID: 34117
URI: http://eprints.soton.ac.uk/id/eprint/34117
ISSN: 1369-1473
PURE UUID: a039d7ed-05a6-467b-a612-ee013e6e072d

Catalogue record

Date deposited: 16 May 2006
Last modified: 17 Jul 2017 15:51

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Contributors

Author: Yves G. Berger
Author: Mohammed E.H. Tirari
Author: Yves Tille

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