Frank,
I'm not sure what is going on. The following test function works for me in both 3.1.1
and 3.2, i.e, the second model matrix has fewer columns. As I indicated to you earlier,
the coxph code removes the strata() columns after creating X because I found it easier to
correctly create the assign attribute.
Can you create a worked example?
require(survival)
testfun <- function(formula, data) {
tform <- terms(formula, specials="strata")
mf <- model.frame(tform, data)
terms2 <- terms(mf)
strat <- untangle.specials(terms2, "strata")
if (length(strat$terms)) terms2 <- terms2[-strat$terms]
X <- model.matrix(terms2, mf)
X
}
tdata <- data.frame(y= 1:10, zed = 1:10, grp = factor(c(1,1,1,2,2,2,1,1,3,3)))
testfun(y ~ zed*grp, tdata)
testfun(y ~ strata(grp)*zed, tdata)
Terry T.
----- original message --
For building design matrices for Cox proportional hazards models in the
cph function in the rms package I have always used this construct:
Terms <- terms(formula, specials=c("strat", "cluster", "strata"), data=data)
specials <- attr(Terms, 'specials')
stra <- specials$strat
Terms.ns <- Terms
if(length(stra)) {
temp <- untangle.specials(Terms.ns, "strat", 1)
Terms.ns <- Terms.ns[- temp$terms] #uses [.terms function
}
X <- model.matrix(Terms.ns, X)[, -1, drop=FALSE]
The Terms.ns logic removes stratification factor "main effects" so that
if a stratification factor interacts with a non-stratification factor,
only the interaction terms are included, not the strat. factor main
effects. [In a Cox PH model stratification goes into the nonparametric
survival curve part of the model].
Lately this logic quit working; model.matrix keeps the unneeded main
effects in the design matrix. Does anyone know what changed in R that
could have caused this, and possibly a workaround?
-------
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