> 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
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