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Conditional and unconditional models in model-assisted estimation of finite population totals

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posted on 2024-11-14, 01:10 authored by David SteelDavid Steel, Robert Clark
The well known Godambe-Joshi lower bound for the anticipated variance of design unbiased estimators of population totals treats the auxiliary variables as constants. We extend the result to models where these variables are random and show that the generalized difference estimator using the expected values conditional on all auxiliary values is optimal. This has several implications including the fact that collecting multiple survey variables does not reduce the lower bound.

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Citation

Steel, D. G. & Clark, R. Graham. (2011). Conditional and unconditional models in model-assisted estimation of finite population totals. Pakistan Journal of Statistics, 27 (4), 529-541.

Journal title

Pakistan Journal of Statistics

Volume

27

Issue

4

Pagination

529-541

Language

English

RIS ID

44131

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