mcl models, percentages

A caveat is that "clogit" in R doesn't produce the same estimates as
"multilog", although the likelihood functions for both models are the
same. The maximum absolute difference is 0.0034, the mean absolute
difference is 0.00069. Stata's "clogit" and "mlogit" produce the same
estimates and match those of "multilog" to at least 6 decimal points
accuracy. See the notes in http://www.xs4all.nl/~jhckx/R/mcl.html Can
anyone shed any light on this?

Two possibilities

1/ not having converged far enough: the convergence tolerance for coxph is
by default only 1e-4 (yes, I should change it)

2/ Weights. In one of your examples you have frequency weights passed to
clogit.  This doesn't work (at least, it isn't equivalent to passing in
the expanded data) because weighting doesn't make coxph compute the full
set of permutations that you need for the likelihood in a large stratum.


	-thomas