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A (Partially) Model-Based Look at Jackknife Variance Estimation with Two-Phase Samples

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  • Kott, Phillip S.

Abstract

This paper focuses on a design-consistent regression estimator in which the “auxiliaries” are estimated from a stratified cluster sample and the regression coefficients from an arbitrary subsample of the original sample. The reweighted expansion estimator described in Stukel and Kott (1997) is an example of such an estimator. Assuming that the target variable is a linear function of the auxiliaries plus an error term, asymptotic properties for both this estimator and the jackknife estimator of its mean squared error are developed. These theoretical results are used to explain some of Stukel and Kott’s empirical findings, which in turn shed light on the asymptotic underpinnings of the theoretical results.

Suggested Citation

  • Kott, Phillip S., 1997. "A (Partially) Model-Based Look at Jackknife Variance Estimation with Two-Phase Samples," NASS Research Reports 234300, United States Department of Agriculture, National Agricultural Statistics Service.
    • Handle: RePEc:ags:unasrr:234300
    DOI: 10.22004/ag.econ.234300
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    Cited by:

    1. repec:ags:unassr:235089 is not listed on IDEAS
    2. Kott, Phillip S., 2001. "Using the Delete-a-Group Jackknife Variance Estimator in NASS Surveys," NASS Research Reports 235089, United States Department of Agriculture, National Agricultural Statistics Service.

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    Keywords

    Agribusiness;

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