model.frame and predvars

I was looking at how the model.frame method for lm works and comparing
it to my own for coxph.
The big difference is that I try to retain xlevels and predvars
information for a new model frame, and lm does not.
I use a call to model.frame in predict.coxph, which is whyI went that
route, but never noted the difference till now (preparing for my course
in Nashville).

Could someone shed light on the rationale for non-preservation?

Terry T.


Simple example

 > library(survival)

 > lfit <- lm(time ~ factor(ph.ecog) + ns(age, 3), data=lung)
 > ltemp <- model.frame(lfit, data=lung[1:2,])
 > ltemp

time factor(ph.ecog) ns(age, 3).1 ns(age, 3).2 ns(age, 3).3
1 306 1 -0.1428571 0.4285714 0.7142857
2 455 0 0.0000000 0.0000000 0.0000000

 > lfit$model[1:2,]

time factor(ph.ecog) ns(age, 3).1 ns(age, 3).2 ns(age, 3).3
1 306 1 0.4443546 0.3286161 0.1900511
2 455 0 0.5697239 0.3618440 -0.1297479

 > levels(ltemp[[2]])

[1] "0" "1"

 > levels(lfit$model[[2]])

[1] "0" "1" "2" "3"

 > cfit <- coxph(Surv(time, status) ~ factor(ph.ecog) + ns(age,3), lung)
 > model.frame(cfit, data= lung[1:2,])

Surv(time, status) factor(ph.ecog) ns(age, 3).1 ns(age, 3).2 ns(age, 3).3
1 306 1 0.4443546 0.3286161 0.1900511
2 455 0 0.5697239 0.3618440 -0.1297479