I posed a question about how to set up the code for this question here (Psychometrics: Survival analysis of help seeking behaviors) and @Fomite suggested that I pose a separate question about whether my data are set up correctly.
I'm studying people seeking help. Participants described contacts with between 1 and 3 "responders" (e.g., friends, the police) in order- for example, a participant could have contacted just responder 1, or responder 1, then responder 2, then responder 3. I'm trying to predict help-seeking dropout, meaning that, for example, a participant contacted responder 1 but did not go on to contact a second or third responder- that participant would have a dropout at responder 1. So unlike other survival analysis, the observations are responders rather than time points- but they're still ordered in time. The independent variables in my model include characteristics of the people seeking help (e.g., gender) and aspects of their interactions with the responders (e.g., whether they liked the interaction). The data are right-censored for those participants who said that they contacted more than three responders because they could not record more than three responders in the survey. There are two people who only reported on responder 3; those people are left-censored because data are missing for responders 1 and 2.
Current data setup:
The data are set up as a person-period dataset such that there is a line for each responder, which means that most participants have multiple lines. Responders are nested within participants. So a participant that contacted two responders would have two lines in the dataset; the participant-level data is the same in both lines and the responder-level data is different.
Here's what the data looks like now: https://flic.kr/p/s1fW6k
@Fomite pointed out that, the way I've set up my data, each responder with a 0 value for stoppedhelpseeking will have a censored event time. This doesn't sound like what I want- what I'm hoping to predict is the point at which people drop out of help-seeking. Censoring should occur at the participant level, not the responder level. What's the right way to set this up to model things correctly?