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Re: st: Competing Cause Mortality
At 22.09 02/06/04 +0300, you wrote:
I have not yet read the paper you refer to but will do so. Meanwhile:
I wonder how the technique cited handles death as a competing
Lunn states that her technique doesn't relax the independence assumption
Fine and Gray (1999 - J. of the Am Stat Association , 94, p. 496-509)
propose a proportional hazard model where the cumulative incidences are
compared. Actually the main advantage of the Fine and Gray's model is that
we can see and test the effect of each covariate on the cumulative
incidence curves and this could be different from the effects we estimate
in an usual Cox model.
Shawn's question was on mortality. If death from competing causes is
handled as censored, Cox will not give the right answer. When a subject is
censored from analysis, he or she is still modeled as being at risk of the
event of interest. However, if the patient died, he or she will not be at
risk of further events, and Cox normally produces an overestimate of
I other words, how does the result of this method compare with the one
obtained with competing risks proportional hazards regression, the
competing risk equivalent of Cox regression.
As far as I know, at present Fine and Gray wrote their codes only in R and
there are not papers other than the previous one where Cox and Fine-Gray
models are compared.
My personal hope is that Stata Authors could add this feature in a next
future as competing-risks data, and the problems they arise, are very
common in medical research.
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