%0 Journal Article %1 busing1999deletem %A Busing, Frank M.T.A. %A Meijer, Erik %A Van Der Leeden, Rien %D 1999 %I Kluwer Academic Publishers %J Statistics and Computing %K bootstrap jackknife nonparametric statistics %N 1 %P 3-8 %R 10.1023/A:1008800423698 %T Delete-m Jackknife for Unequal m %U http://dx.doi.org/10.1023/A%3A1008800423698 %V 9 %X 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.

@article{busing1999deletem, 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.}, added-at = {2015-03-04T19:05:07.000+0100}, author = {Busing, Frank M.T.A. and Meijer, Erik and {Van Der Leeden}, Rien}, biburl = {https://www.bibsonomy.org/bibtex/2433747cb6aec7419a4d1cb0a1d8a6da5/peter.ralph}, doi = {10.1023/A:1008800423698}, interhash = {37320a06904cef81cf20d4e27a78efe2}, intrahash = {433747cb6aec7419a4d1cb0a1d8a6da5}, issn = {0960-3174}, journal = {Statistics and Computing}, keywords = {bootstrap jackknife nonparametric statistics}, language = {English}, number = 1, pages = {3-8}, publisher = {Kluwer Academic Publishers}, timestamp = {2015-03-04T19:05:07.000+0100}, title = {Delete-m Jackknife for Unequal m}, url = {http://dx.doi.org/10.1023/A%3A1008800423698}, volume = 9, year = 1999 }