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Title: Bias in estimating association parameters for longitudinal binary responses with drop-outs.

Authors: Fitzmaurice, G M; Lipsitz, S R; Molenberghs, G; Ibrahim, J G

Published In Biometrics, (2001 Mar)

Abstract: This paper considers the impact of bias in the estimation of the association parameters for longitudinal binary responses when there are drop-outs. A number of different estimating equation approaches are considered for the case where drop-out cannot be assumed to be a completely random process. In particular, standard generalized estimating equations (GEE), GEE based on conditional residuals, GEE based on multivariate normal estimating equations for the covariance matrix, and second-order estimating equations (GEE2) are examined. These different GEE estimators are compared in terms of finite sample and asymptotic bias under a variety of drop-out processes. Finally, the relationship between bias in the estimation of the association parameters and bias in the estimation of the mean parameters is explored.

PubMed ID: 11252590 Exiting the NIEHS site

MeSH Terms: Algorithms; Bias*; Biometry; Humans; Longitudinal Studies*; Models, Statistical

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