  Brad Efron's paper [arXiv:0808.0572] has inspired a return to the ideas
behind Bayes, frequency and empirical Bayes. The latter preferably would not be
limited to exchangeable models for the data and hyperparameters. Parallels are
revealed between microarray analyses and profiling of hospitals, with advances
suggesting more decision modeling for gene identification also. Then good
multilevel and empirical Bayes models for random effects should be sought when
regression toward the mean is anticipated.
