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 [[alternative HTML version deleted]]