Greetings!
I have a quick question about Cox models: I understand that we need to
test for the assumption of proportional hazards for all covariates,
and if any one fails the test, we should be concerned about the
statistical inference on that variable; plus we should consider things
such as time varying effects, stratification, and so on. But what if
none of these solves the problem? In particular, is it appropriate to
say that if one set of variables passes the test, we can still be
confident about the estimates of their coefficients - despite the
failure of other variables and global tests? In other words, while we
know that Cox models tend to be quite robust, how much latitude do we
have in terms of the proportional hazards assumption? How robust is
this model, just to be specific?
I'm still learning event history analysis, and the papers that I have
came across so far (empirical papers in social sciences) do not seem
to actually test that assumption (or maybe they forgot to report the
results), so I am just curious.
Thank you very much for any suggestions you can provide. If you could
refer me to specific papers on this, it would be really helpful.
Mingfeng
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