[Rd] model.matrix and subset
Therneau, Terry M., Ph.D.
therne@u @end|ng |rom m@yo@edu
Tue Mar 22 15:47:39 CET 2022
Yes, the predict functions do not use model.frame(fit), rather they extract the terms, as
you say. I do the same in predict.coxph.
One way to address my question would be for the documentation of model.frame and
model.matrix to explicitly state what they currently do when data= is specified, i.e.,
that any subset or na.action clauses in the original call will be applied to the new data
as well. It still won't be what a user might expect, but it might keep future users out
Of course, when there is no data= clause, a user will expect the original data set; which
impllies retaining any subset= arguments in that instance.
On 3/22/22 09:04, peter dalgaard wrote:
> AFAICT, predict.lm does effectively this:
> Terms <- delete.response(terms(fit))
> m <- model.frame(Terms, data2)
> model.matrix(Terms, m)
> except for some embellishments that I can't quite grasp at this point.
> I expect that this is to circumvent similar issues.
> - pd
>> On 21 Mar 2022, at 17:43 , Therneau, Terry M., Ph.D. via R-devel<r-devel using r-project.org> wrote:
>> I've found the following unexpected behaviour from the model.matrix function, namely that
>> the "subset" argument carries forward when I would not expect it to.
>> Here is an example using lm:
>> # Data set modified from the lm help file
>> test <- data.frame(weight= c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14,
>> group = gl(2, 10, 20, labels = c("Ctl","Trt")),
>> zed = rep (1:2, 10))
>> fit <- lm( weight ~ group, test, subset= (zed==1))
>> data2 <- data.frame( weight= 1:6, group= rep(c("Ctl", "Trt"), 3))
>> model.matrix (fit, data=data2)
>> Error in eval(substitute(subset), data, env) : object 'zed' not found
>> This arises out a user's bug report for survival::concordance; which has methods for
>> formula, lm, glm, and coxph. I have been using model.frame and model.matrix to create
>> the new response and linear predictor when a 'newdata' argument is used. The above
>> issue makes it fail for all of lm, glm, and coxph when the initial model includes a subset.
>> I think that the user is correct: if someone asks for model.matrix(fit, data=new) they
>> almost certainly want the model matrix for exactly that data. But it leaves me in a bit
>> of a quandry. I don't want to write private model.matrix methods for glm and lm, and if
>> I fix the coxph methods then they will disagree with the standard ones.
>> Terry M Therneau, PhD
>> Department of Quantitative Health Sciences
>> Mayo Clinic
>> therneau using mayo.edu
>> "TERR-ree THUR-noh"
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>> R-devel using r-project.org mailing list
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