Bias in estimating association parameters for longitudinal binary responses with drop-outs |
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Authors: | Fitzmaurice G M Lipsitz S R Molenberghs G Ibrahim J G |
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Institution: | Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. |
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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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Keywords: | Generalized estimating equations Missing data Repeated measures |
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