Correlated binary regression with covariates specific to each binary observation. (English) Zbl 0715.62145

Summary: Regression methods are considered for the analysis of correlated binary data when each binary observation may have its own covariates. It is argued that binary response models that condition on some or all binary responses in a given “block” are useful for studying certain types of dependencies, but not for the estimation of marginal response probabilities or pairwise correlations. Fully parametric approaches to these latter problems appear to be unduly complicated except in such special cases as the analysis of paired binary data. Hence, a generalized estimating equation approach is advocated for inference on response probabilities and correlations. Illustrations involving both small and large block sizes are provided.


62J99 Linear inference, regression
62P10 Applications of statistics to biology and medical sciences; meta analysis
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