[R] [UNCLASSIFIED] predict.survreg() with frailty term and newdata

joe.crombie at affa.gov.au joe.crombie at affa.gov.au
Mon Jan 22 01:03:40 CET 2007

Dear All,
I am attempting to make predictions based on a survreg() model with some censoring and a frailty term, as below:  predict works fine on the original data, but not if I specify newdata.
# a model with groups as fixed effect
model1 <- survreg(Surv(y,cens)~ x1 + x2 + groups,
                 dist = "gaussian")

# and with groups as a random effect
fr <- frailty(groups, dist = "gaussian", sparse = F)
model2 <- survreg(Surv(y,cens)~ x1 + x2 + fr,
                  dist = "gaussian")

# predict() works fine for groups as fixed effect
predict(model1, newdata = list(x1 = 1, x2 = 1, groups = groups[1]))
#       [,1]
# 1 10.51833  # no problem!

# but not so well with frailty(groups)
predict(model2, newdata = list(x1 = 1, x2 = 1, fr = factor(1, levels = 1:10)))
#> Error in x %*% coef : non-conformable arguments

I have found references on the R and S-Plus lists which suggest that others have had this problem (in both packages), but I can't find any solution or further explanation.  Can anyone suggest a way of getting the predictions I'm after?  Any help is greatly appreciated.
Kind regards  Joe
Joe Crombie
Information and Risk Sciences
Bureau of Rural Science
Canberra  Australia
p: +61 2 6272 5906
e: joe.crombie at brs.gov.au <blocked::mailto:joe.crombie at brs.gov.au> 

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