I'm trying to implement survival analysis on conversion rates for a free trial product we provide. In general, I understand the applications on survival analysis along with dealing with right censored data (e.g., if a customer is currently on trial, we don't really know if they will or will not convert in the future).

My question is, how do you implement a survival analysis model in this context if you know the trial ends in 14 days? So you may have a handful of customers that simply leave the early (these would indicate a 'death'), and you have many who are currently in the trial (these are the censored customers). How would you go about modeling this knowing that the trial can't go on to some uncertain time in the future? it must end at some point in the future (14 days in my examples).

Also what sort of variables I can include based on your insight/knowledge/intuition.

Thanks in advance

  • $\begingroup$ You could treat the event of "leaving early" as a competing risk event which precludes the ocurrence of the event of interest (i.e., "conversion by the end of the trial period) and use a competing risks framework to analyze your data. Also, see ncbi.nlm.nih.gov/pmc/articles/PMC2811964. $\endgroup$ – Isabella Ghement Jun 20 '19 at 8:23

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