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

Phillip S. Kott and Steven T. Garren

No 234370, NASS Research Reports from United States Department of Agriculture, National Agricultural Statistics Service

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.

Keywords: Agribusiness; Research Methods/Statistical Methods (search for similar items in EconPapers)
Pages: 18
Date: 2009-05
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Persistent link: https://EconPapers.repec.org/RePEc:ags:unasrr:234370

DOI: 10.22004/ag.econ.234370

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