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Evaluating the Asymptotic Limits of the Delete-a-Group Jackknife for Model Analyses

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  • Kott, Phillip S.
  • Garren, Steven T.

Abstract

The delete-a-group jackknife can be effectively used when estimating the variances of statistics based on a large sample. The theory supporting its use is asymptotic, however. Consequently, analysts have questioned its effectiveness when estimating parameters for a small domain computed using only a fraction of the large sample at hand. We investigate this issue empirically by focusing on heavily poststratified estimators for a population mean and a simple regression coefficient, where the poststratification takes place at the full-sample level. Samples are chosen using differentially-weighted Poisson sampling. The bias and stability of delete-a-group jackknife employing either 15 or 30 replicates are evaluated and compared with the behavior of linearization variance estimators.

Suggested Citation

  • Kott, Phillip S. & Garren, Steven T., 2009. "Evaluating the Asymptotic Limits of the Delete-a-Group Jackknife for Model Analyses," NASS Research Reports 234370, United States Department of Agriculture, National Agricultural Statistics Service.
    • Handle: RePEc:ags:unasrr:234370
    DOI: 10.22004/ag.econ.234370
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    1. 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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