Closed Xueke1001 closed 1 year ago
It is difficult to determine initial values for Royston-Parmar models sometimes. If this error happens you will have to specify the inits
argument to flexsurvspline
by hand, and try to identify initial values which will give a non-zero likelihood (i.e. a finite log likelihood).
You could fit a Weibull model as a starting point, since the flexsurvspline
model with k=0 is equivalent to a Weibull. Then determine what gamma0 and gamma1 should be in terms of the Weibull shape and scale (see help(flexsurvspline)). That should get you a working flexsurvspline
model with k=0.
Then try to build up the spline complexity bit by bit, starting with k=1
say with those initial values for gamma0 and gamma1, and setting gamma2=0, etc... The covariate effects should not be very different for different k.
Thank you, that's very helpful
Hi Chris,
I worked with
flexsurvspline
and tried to figure out incident rate using age as time-scale.I used brcancer data and coded as following:
flexsurvspline(Surv(age_in,age_out,censrec)~hormon,type="interval2",data=brcancer,k=3)
then I got a warning "Error in optim(type = "interval2", method = "BFGS", par = c(gamma0 = 0, : initial value in 'vmmin' is not finite"I did similar analysis with
flexsurvreg
and it worked.flexsurvreg(Surv(age_in,age_out,censrec)~hormon,data=brcancer,dist="gompertz")
Can this be attained by
flexsurvspline
?Thanks in advance
XK