Delete-m Jackknife for Unequal m View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1999-04

AUTHORS

Frank M. T. A. Busing, Erik Meijer, Rien Van Der Leeden

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. More... »

PAGES

3-8

Journal

TITLE

Statistics and Computing

ISSUE

1

VOLUME

9

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1008800423698

DOI

http://dx.doi.org/10.1023/a:1008800423698

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1002000075


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