The BLUPs are not "best" when it comes to bootstrapping
AbstractIn the setting of mixed models, some researchers may construct a semiparametric bootstrap by sampling from the best linear unbiased predictor residuals. This paper demonstrates both mathematically and by simulation that such a bootstrap will consistently underestimate the variation in the data in finite samples.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 56 (2002)
Issue (Month): 4 (February)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Shang, Junfeng & Cavanaugh, Joseph E., 2008. "An assumption for the development of bootstrap variants of the Akaike information criterion in mixed models," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1422-1429, September.
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