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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