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A pairwise likelihood approach to analyzing correlated binary data

โœ Scribed by Anthony Y.C. Kuk; David J. Nott

Publisher
Elsevier Science
Year
2000
Tongue
English
Weight
85 KB
Volume
47
Category
Article
ISSN
0167-7152

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โœฆ Synopsis

The method of pairwise likelihood is investigated for analyzing clustered or longitudinal binary data. The pairwise likelihood is a product of bivariate likelihoods for within cluster pairs of observations, and its maximizer is the maximum pairwise likelihood estimator. We discuss the computational advantages of pairwise likelihood relative to competing approaches, present some e ciency calculations and argue that when cluster sizes are unequal a weighted pairwise likelihood should be used for the marginal regression parameters, whereas the unweighted pairwise likelihood should be used for the association parameters.

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