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Regression models for longitudinal binary responses with informative drop-outs. (English) Zbl 0827.62060
Summary: This paper reviews both likelihood-based and non-likelihood (generalized estimating equations) regression models for longitudinal binary responses when there are drop-outs. Throughout, it is assumed that the regression parameters for the marginal expectations of the binary responses are of primary scientific interest. The association or time dependence between the responses is largely regarded as a nuisance characteristic of the data. The performance of the methods is compared, in terms of asymptotic bias, under misspecification of the association between the responses and the missing data mechanism or drop-out process.

MSC:
62J12 Generalized linear models (logistic models)
62J99 Linear inference, regression
62H12 Estimation in multivariate analysis
62P10 Applications of statistics to biology and medical sciences; meta analysis
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