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Bootstrapping clustered data

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  • C. A. Field
  • A. H. Welsh
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    Abstract

    Various 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.

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    Bibliographic Info

    Article 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 ()
    Pages: 369-390

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    Handle: RePEc:bla:jorssb:v:69:y:2007:i:3:p:369-390

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    Cited by:
    1. 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.
    2. Mathieu Bunel, 2012. "Evaluer un dispositif sectoriel d’aide à l’emploi : L’exemple des hôtels cafés restaurants de 2004 à 2009," TEPP Research Report 2012-03, TEPP.
    3. Mathieu Bunel & Yannick L'Horty, 2011. "Les effets des aides publiques aux Hôtels Cafés Restaurants et leurs interactions : Une évaluation sur micro-données d’entreprises," TEPP Research Report 2011-10, TEPP.
    4. 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.
    5. 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.
    6. 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.
    7. Orth, Walter, 2013. "Multi-period credit default prediction with time-varying covariates," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 214-222.
    8. Mathieu Bunel & Yannick L'Horty, 2011. "Les effets des aides publiques aux Hôtels Cafés Restaurants et leurs interactions," Working Papers halshs-00658460, HAL.
    9. Orth, Walter, 2011. "Multi-period credit default prediction with time-varying covariates," MPRA Paper 30507, University Library of Munich, Germany.
    10. 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.
    11. 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.
    12. 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.

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