Good morning,
Sorry to trouble the list. I'm working on Cox models of survival, and
am encountering a problem. I'm trying to group variables into some
kind of new staging system By grouping, I mean : so-called
'integrated staging systems' for cancer merge categories of variables
such as tumor stage, patient status into a single range of categories
e.g.
System I = Stage I or II, Patient Status 0
System II = Stage I or II, Patient Status 1
OR
Stage III, Patient Status 0
So in this example, Stage I + II are grouped together, probably based
on outcome.
So in the scenario where each of the initial 2 variables A and B
involved in the model have 4 categories:
1. Is there any other way to obtain a grouping the variables by
outcome besides examining all possible 16 Kaplan Meier curves
concurrently, and seeing how they group? Would it make sense to run
pairwise survfits - but if so, what happens when more variables are
introduced into the equation? Finally, is it possible to execute this
in R? Thanks!!!
2. If there is a significant interaction between these 2 terms (A*B),
does it even make sense to ask how I can perform "grouping" of the
variables?
Thanks in advance!
Min-Han
