Thanks. Here are some examples of my data structure. Say the study period is until 2013-12-31 as in ID 1. But if there's a change in any subject due to some time-dependent variable (treatment / as in ID 2 and 3), I updated the attribute before and after the date of the change as in Table 1. Table 1. ID startdate1 enddate1 treatment1 outcome1 startdate2 enddate2 treatment1 outcome2 1 2013-05-01 2013-12-31 0 0 . . . . 2 2013-06-01 2013-06-30 0 0 2013-06-30 2013-11-20 1 0 3 2013-07-01 2013-07-30 0 0 2013-07-30 2013-12-01 1 1 In order to run this through PROC PHREG, I changed the dataset into long form as following table 2. (i.e, those who have different states have 2 rows) Table 2. ID start end treatment outcome 1 2013-05-01 2013-12-31 0 0 2 2013-06-01 2013-06-30 0 0 2 2013-06-30 2013-11-20 1 0 3 2013-07-01 2013-07-30 0 0 3 2013-07-30 2013-12-01 0 1 and the code goes as: proc phreg data=sample; class treatment (ref='0'); model (start, end)*outcome(0) = treatment / rl; strata OOO (some other adjusting variables); run; But when I run this code, it takes several hours to get the results. (original dataset has about 10 million records) So instead using (start, end) form, I manually calculated the time-to-event (tte) as following table 3 Table 3. ID tte treatment outcome 1 244 0 0 2 29 0 0 2 143 1 0 3 29 0 0 3 124 0 1 and only changed the (start, end) part into "tte" as : proc phreg data=sample; class treatment (ref='0'); model tte*outcome(0) = treatment / rl; strata OOO (some other adjusting variables); run; In this case, the program only takes minutes, but the results are different from when using (start, end) statement. (sorry that I don't have exact numbers since I'm running another program right now) * I referred to http://support.sas.com/resources/papers/proceedings12/168-2012.pdf this article when managing the dataset, though it doesn't say anything about whether manually calculating the time-to-event will result the same or not. hope this explains enough to ask for your help.
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