I am using psm to fit a survival model with a dataset that has missing
values,
e.g., DS <-psm(Surv(los,DSCHRG) ~AGE + SEX + ACUITY,
data=LOS,dist='weibull',x=TRUE,y=TRUE)
and I notice that when I look at the output there are 0 missing values and
when I use the summary function
e.g., summary(DS) plot(summary(DS))
the missing values are showing up as a category
e.g., for Sex
F:
F:M
Do the missing values need to be coded as NA, instead of just being left
empty?
If so is there a quick way to do this?
Thank You,
Spencer
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