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

G M Fitzmaurice; S R Lipsitz; G Molenberghs; J G Ibrahim

doi:10.1111/j.0006-341x.2001.00015.x

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

G M Fitzmaurice·S R Lipsitz·G Molenberghs·J G Ibrahim

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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.

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Algorithms Bias Biometry Humans Longitudinal Studies Models, Statistical Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.

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G M Fitzmaurice, S R Lipsitz, G Molenberghs, J G Ibrahim. 2001. Bias in estimating association parameters for longitudinal binary responses with drop-outs.. https://doi.org/10.1111/j.0006-341x.2001.00015.x

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