I am trying to run Kaplan-Meier on a rather odd dataset and am having difficulty determining whether I should be truncating or censoring my data. I have looked at the other feeds, including this very helpful one, but I am still confused and want to make sure my line of reasoning isn't off.
The dataset is a sample of individuals with age-at-death data ranging from birth to old age. I have a few populations from different cities, effectively. I would like to evaluate overall pattern of survivorship (across the lifecourse) between the two cities. However, I would also like to identify whether there are significant differences in survivorship between the cities for demographic segments - survivors and nonsurvivors (divided at age 18).
To look at non-survivors (those under 18) it seems to me that I should right-censor since I am factoring out the adults who have survived that period. To focus on the adult period, though, would I left truncate since I am artificially cutting out those who died before 18 years of age? If it is left truncated, would I just eliminate those entirely from my analysis before I run Kaplan-Meier?
I am not a statistician by any means and this one is really throwing me. Any advice would be most appreciated!