Perform simultaneous estimation and variable selection for correlated bivariate mixed outcomes (one continuous outcome and one binary outcome per cluster) using penalized generalized estimating equations. In addition, clustered Gaussian and binary outcomes can also be modeled. The SCAD, MCP, and LASSO penalties are supported. Cross-validation can be performed to find the optimal regularization parameter(s).
Deshpande, V., Dey, D. K., and Schifano, E. D. (2016). Variable selection for correlated bivariate mixed outcomes using penalized generalized estimating equations. Technical Report 16-23, Department of Statistics, University of Connecticut, Storrs, CT.
Wang, L., Zhou, J., and Qu, A. (2012). Penalized generalized estimating equations for high-dimensional longitudinal data analysis. Biometrics, 68, 353<e2><80><93>360.
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