Simultaneous confidence bands using model assisted Cox regression

In the first part, entitled “Model assisted Cox regression” and published in Journal of Multivariate Analysis (JMVA), it was shown that standard Cox regression, combined with Dikta’s semiparametric random censorship models, provides an effective framework for obtaining improved parameter estimates. Here, this methodology is exploited to construct simultaneous confidence bands (SCBs) for subject-specific survival curves. Simulation results are presented to compare the performance of the proposed SCBs with the SCBs that are based only on standard Cox. The new SCBs provide correct empirical coverage and are more informative. The proposed SCBs are illustrated with two real examples. An extension to handle missing censoring indicators is also outlined.