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I'm monitoring a website where I have two kinds of users (say, A and B). These users are able to contribute to this site in a variety of ways and, for each contribution, its time is logged. What I want is to compare if the number of days that the user is active (contributing in some way) differ between the kinds of users.

I'm monitoring the website since it's beginning until four months ago. Not all users joined as soon as the site was created nor users that joined at the beginning are still contributing.

Is survival analysis suitable for this comparison ?

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No. Survival analysis is for time to event data. You want to compare "number of days active" which is a count variable. You want to control (or seem to want to control) for number of days that the user might have contributed - number of days "joined".

This suggests a count regression (Poisson, negative binomial or variation) with "type of user" and "number of days joined" as independent variables.

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    $\begingroup$ She mentioned that some users are not contributing anymore, i.e. inactive. In this case maybe they should not be counted in. This sounds like survival analysis aspect to me. $\endgroup$ – Aksakal Apr 9 '14 at 19:19
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    $\begingroup$ No, because she isn't modeling whether they are in or not - that is a covariate not the dependent variable $\endgroup$ – Peter Flom - Reinstate Monica Apr 9 '14 at 19:56
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    $\begingroup$ I guess I got it. I would use survival analysis if I wanted to know if users A stop contributing earlier than users B, if I knew when they stopped contributing. Is that correct ? $\endgroup$ – Milena Araujo Apr 9 '14 at 21:08
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    $\begingroup$ Yes, exactly. Survival analysis deals with time to event data; it is particularly helpful when, as is often the case, some subjects are censored. $\endgroup$ – Peter Flom - Reinstate Monica Apr 9 '14 at 22:06

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