I would like to model a recurrent event with subjects that move in and out of risk over the course of the observation period of the study.
I have data on the out-of-risk periods (start and end dates) where the subject cannot experience the event. In my reading of this topic, I believe that this situation is referred to as "interval truncation" or "gaps", where subjects are "unobserved" for periods. And to best represent this, my data should be structured in counting process format, with start stop times that reflect these "gaps" in observations of each subject.
Q1. I would like to confirm that my understanding is correct and this would be an appropriate approach? If not, suggestions of better approaches are welcomed!
Q2. If interval truncation is the way to go, I would appreciate any help on how to convert my data to this counting process format with start stop times that reflect both event occurrence and unobserved periods in R. I can convert the data to counting process format with event occurrence, but do not know how to partition my start stop times to reflect unobserved periods (other than manually creating the data set which I would very much like to avoid).
Other useful info about my study:
- Subjects have a common start time of 0 months.
- Subjects are right-censored.
- Subjects are observed for 3 years.
- Subjects can move in and out of risk for varying amounts of time and frequency during the 3 year observation period.