Delete-m Jackknife for Unequal m (original) (raw)
Abstract
In this paper, the delete-mj jackknife estimator is proposed. This estimator is based on samples obtained from the original sample by successively removing mutually exclusive groups of unequal size. In a Monte Carlo simulation study, a hierarchical linear model was used to evaluate the role of nonnormal residuals and sample size on bias and efficiency of this estimator. It is shown that bias is reduced in exchange for a minor reduction in efficiency. The accompanying jackknife variance estimator even improves on both bias and efficiency, and, moreover, this estimator is mean-squared-error consistent, whereas the maximum likelihood equivalents are not.
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Authors
- Frank M. T. A. Busing
You can also search for this author inPubMed Google Scholar - Erik Meijer
You can also search for this author inPubMed Google Scholar - Rien Van Der Leeden
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Busing, F.M.T.A., Meijer, E. & Leeden, R.V.D. Delete-m Jackknife for Unequal m.Statistics and Computing 9, 3–8 (1999). https://doi.org/10.1023/A:1008800423698
- Issue Date: April 1999
- DOI: https://doi.org/10.1023/A:1008800423698