...
> Occasionally, (about 1 in every 100 simulations) I get the following warning:
> Error in coxph(Surv(start, end, censorind) ~ binary + uniform :
> X matrix deemed to be singular; variable 2
It is not uncommon for the X matrix in a Cox model to be close enough to
singular that the program thinks it is singular, i.e., one of the pivot
elements
falls below the tolerance threshold while performing a Cholesky decomposition.
To understand your case better you need to capture one of the offending data
sets and look at the X matrix. I am not going to be able to guess.
I normally ignore this (the indeterminate coefficient is set to NA) and go
on. You however have chosen to override the default and set singular.ok=FALSE
so that the program fails with an error message. You get what you asked for.
Last, I am always surprised when people chose method='breslow' in coxph. Why
substitute an inferior approximation for the better one? Of course with
simulated data there are no ties, in which case all the methods are identical.
Terry Therneau
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