PGEE (with R code)

We have proposed penalized generalized estimating equations with Elastic Net or L2-Smoothly Clipped Absolute Deviation penalization to simultaneously select the most important variables and estimate their effects for longitudinal Gaussian data when multicollinearity is present. The method is able to consistently select and estimate the main effects even when strong correlations are present. In addition, the potential pitfall of time-dependent covariates is clarified.

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