> survmod <- survreg(Surv(sapply(bleedtimes, min, 10), bleedtimes < 10) > ~ device + frailty.gaussian(pat))
> residuals(survmod) > Error in residuals.survreg.penal(survmod) : > Residuals not available for sparse models Thanks for the reproducable error. a. With respect to your earliest question, the "pterms" attributes in a survreg model are used to keep track of penalized terms. Smoothing splines and frailties are implimented in this way. b. A gaussian frailty with the default "reml" method does not work correctly with survreg. See the manual page help('frailty'). c. You could use frailty.gaussian(pat, sparse=1000, method='aic'). The first argument avoids the use of a sparse approximation (your example had 32 patients which is < 1000), the second uses AIC to choose the size of the random effect. I had forgotton that extension of the residuals to the sparse case was an addition that I never finished. With 100 or fewer groups the full computation is not usually a burden, the sparse matrix approximations were mostly designed for genetics studies where I have thousands of subjects. Terry Therneau ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.