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Summary We consider the penalized generalized estimating equations (GEEs) for analyzing longitudinal data with high‐dimensional covariates, which often arise in microarray experiments and large‐scale health studies. Existing high‐dimensional regression procedures often assume independent data and rely on the likelihood function. Construction of a feasible joint likelihood function for high‐dimensional...
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