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Orthogonalized residuals for estimation of marginally specified association parameters in multivariate binary data.

ABSTRACT: This paper focuses on marginal regression models for correlated binary responses when estimation of the association structure is of primary interest. A new estimating function approach based on orthogonalized residuals is proposed. A special case of the proposed procedure allows a new representation of the alternating logistic regressions method through marginal residuals. The connections between second-order generalized estimating equations, alternating logistic regressions, pseudo-likelihood and other methods are explored. Eficiency comparisons are presented, with emphasis on variable cluster size and on the role of higher-order assumptions. The new method is illustrated with an analysis of data on impaired pulmonary function.

SUBMITTER: Qaqish BF

PROVIDER: S-EPMC3501755 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Orthogonalized residuals for estimation of marginally specified association parameters in multivariate binary data.

Qaqish Bahjat F BF Zink Richard C RC Preisser John S JS

Scandinavian journal of statistics, theory and applications 20120702 3

This paper focuses on marginal regression models for correlated binary responses when estimation of the association structure is of primary interest. A new estimating function approach based on orthogonalized residuals is proposed. A special case of the proposed procedure allows a new representation of the alternating logistic regressions method through marginal residuals. The connections between second-order generalized estimating equations, alternating logistic regressions, pseudo-likelihood a ...[more]

PMID: 23180903

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