Bootstrapping clustered data
AbstractVarious bootstraps have been proposed for bootstrapping clustered data from one-way arrays. The simulation results in the literature suggest that some of these methods work quite well in practice; the theoretical results are limited and more mixed in their conclusions. For example, McCullagh reached negative conclusions about the use of non-parametric bootstraps for one-way arrays. The purpose of this paper is to extend our understanding of the issues by discussing the effect of different ways of modelling clustered data, the criteria for successful bootstraps used in the literature and extending the theory from functions of the sample mean to include functions of the between and within sums of squares and non-parametric bootstraps to include model-based bootstraps. We determine that the consistency of variance estimates for a bootstrap method depends on the choice of model with the residual bootstrap giving consistency under the transformation model whereas the cluster bootstrap gives consistent estimates under both the transformation and the random-effect model. In addition we note that the criteria based on the distribution of the bootstrap observations are not really useful in assessing consistency. Copyright 2007 Royal Statistical Society.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series B (Statistical Methodology).
Volume (Year): 69 (2007)
Issue (Month): 3 ()
Contact details of provider:
Postal: 12 Errol Street, London EC1Y 8LX, United Kingdom
Web page: http://www.blackwellpublishing.com/journal.asp?ref=1369-7412
More information through EDIRC
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Mathieu Bunel & Yannick L'Horty, 2011. "Les effets des aides publiques aux Hôtels Cafés Restaurants et leurs interactions," Working Papers halshs-00658460, HAL.
- Gilardoni, Gustavo L. & Oliveira, Maristela D. de & Colosimo, Enrico A., 2013. "Nonparametric estimation and bootstrap confidence intervals for the optimal maintenance time of a repairable system," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 113-124.
- Mathieu Bunel, 2012. "Évaluer un dispositif sectoriel d'aide à l'emploi : l'exemple des hôtels, cafés et restaurants de 2004 à 2009," Economics Working Paper Archive (University of Rennes 1 & University of Caen) 201223, Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS.
- Orth, Walter, 2013. "Multi-period credit default prediction with time-varying covariates," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 214-222.
- Orth, Walter, 2011. "Multi-period credit default prediction with time-varying covariates," MPRA Paper 30507, University Library of Munich, Germany.
- Ross Stolzenberg, 2011. "Do Not Go Gentle Into That Good Night: The Effect of Retirement on Subsequent Mortality of U.S. Supreme Court Justices, 1801–2006," Demography, Springer, vol. 48(4), pages 1317-1346, November.
- John Mullahy & Stephanie Robert, 2010. "No time to lose: time constraints and physical activity in the production of health," Review of Economics of the Household, Springer, vol. 8(4), pages 409-432, December.
- Desmarais, B.A. & Cranmer, S.J., 2012. "Statistical mechanics of networks: Estimation and uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1865-1876.
- Orth, Walter, 2010. "The predictive accuracy of credit ratings: Measurement and statistical inference," MPRA Paper 30148, University Library of Munich, Germany, revised 16 Feb 2011.
- Van Oirbeek, R. & Lesaffre, E., 2012. "Assessing the predictive ability of a multilevel binary regression model," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1966-1980.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.