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Towards optimal regression estimation in sample surveys

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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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Keywords: Montanari estimator; conditional Poisson sampling; design-based inference; generalized regression estimator; inclusion probabilities

Document Type: Research Article

Affiliations: 1: University of Southampton 2: Université Libre de Bruxelles 3: Université de Neuchâtel

Publication date: September 1, 2003

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