### Robust Sandwich Variance Estimate

For the ith subject, , let , , and be the observed time, weight, and the covariate vector at time t, respectively. Let be the event indicator and let . Let

Let . The score residual for the ith subject is

For TIES=EFRON, the computation of the score residuals is modified to comply with the Efron partial likelihood. See the section Residuals for more information.

The robust sandwich variance estimate of derived by Binder (1992), who incorporated weights into the analysis, is

where is the observed information matrix, and . Note that when ,

where is the matrix of DFBETA residuals. This robust variance estimate was proposed by Lin and Wei (1989) and Reid and Crèpeau (1985).