Please use this identifier to cite or link to this item: https://doi.org/10.1093/biomet/91.3.758
Title: Permutation invariance of alternating logistic regression for multivariate binary data
Authors: Kuk, A.Y.C. 
Keywords: Clustered data
Conditional residual
Generalised estimating equation
Longitudinal data
Pairwise likelihood
Issue Date: 2004
Citation: Kuk, A.Y.C. (2004). Permutation invariance of alternating logistic regression for multivariate binary data. Biometrika 91 (3) : 758-761. ScholarBank@NUS Repository. https://doi.org/10.1093/biomet/91.3.758
Abstract: A practically important but not so obvious result is that alternating logistic regression is invariant to permutations of the response variables within clusters. In this note, we give a short proof of the invariance result using a pairwise likelihood argument. The same proof can be used to establish invariance for a more general class of estimating equations based on conditional residuals. As it stands, the invariance theory is incomplete because existing standard error estimates are not invariant to permutations. To solve this problem we present a symmetrised version of the estimating equation and use it to obtain permutation-invariant standard errors. © 2004 Biometrika Trust.
Source Title: Biometrika
URI: http://scholarbank.nus.edu.sg/handle/10635/105298
ISSN: 00063444
DOI: 10.1093/biomet/91.3.758
Appears in Collections:Staff Publications

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