Joint model selection of marginal mean regression and correlation structure for longitudinal data with missing outcome and covariates.
Biom J 2017 Sep 14. Epub 2017 Sep 14.
Institute of Statistical Science, Academia Sinica, Taipei, Taiwan, 11529, R.O.C.
This work develops a joint model selection criterion for simultaneously selecting the marginal mean regression and the correlation/covariance structure in longitudinal data analysis where both the outcome and the covariate variables may be subject to general intermittent patterns of missingness under the missing at random mechanism. The new proposal, termed "joint longitudinal information criterion" (JLIC), is based on the expected quadratic error for assessing model adequacy, and the second-order weighted generalized estimating equation (WGEE) estimation for mean and covariance models. Simulation results reveal that JLIC outperforms existing methods performing model selection for the mean regression and the correlation structure in a two stage and hence separate manner. Read More