My outcomes is binary variable. I would like to perform logistic regression model to estimate the treatment effect of Xs. However, the follow up time was longer for outcomes=1 and shorter when outcomes=0. The probability of the outcome can be affected by the follow up time, the longer a subject was followed up, the more chance we observe a outcome=1. I considered including the follow up time as an offset, like poisson regression model. Is it reasonable? Otherwise, how can I control the difference in follow up between the two groups.
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$\begingroup$ I think this question should be in StackOverflow, this post answers to your question: stackoverflow.com/questions/13237940/… Cheers $\endgroup$– Nico CoallierCommented Mar 30, 2016 at 21:09
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$\begingroup$ Might be relevant: stats.stackexchange.com/questions/25415/… stats.stackexchange.com/questions/155575/… stats.stackexchange.com/questions/66792/… $\endgroup$– kjetil b halvorsen ♦Commented Mar 17, 2017 at 19:46
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2$\begingroup$ No, this post belongs here! $\endgroup$– kjetil b halvorsen ♦Commented Mar 17, 2017 at 19:46
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$\begingroup$ This sounds like you may potentially have censoring. What does 1 and 0 represent? $\endgroup$– Glen_bCommented Aug 13, 2017 at 2:05
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