Title: The generalised bootstrap for clustered data

Authors: Zhen Pang; A.H. Welsh

Addresses: Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University, 637371, Singapore ' Centre for Mathematics and its Applications, The Australian National University, Canberra ACT 0200, Australia

Abstract: We extend the generalised bootstrap of Chatterjee and Bose (2005) to bootstrap clustered data. We show by simulations and theoretical arguments that the variance of the random weights used in the generalised bootstrap is critical in determining the performance of the bootstrap when we use the distribution of the bootstrap estimate to approximate the sampling distribution of the parameter. In particular, we show that for consistency, the weights should be chosen to have variance one.

Keywords: data clustering; clustered data; quasi-likelihood estimation; unbalanced data; variance components; generalised bootstrap; simulation; sampling distribution.

DOI: 10.1504/IJDATS.2014.066604

International Journal of Data Analysis Techniques and Strategies, 2014 Vol.6 No.4, pp.407 - 415

Published online: 14 Jan 2015 *

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