Cross Validated Asked by Thomas Richardson on November 9, 2021
So I have data from a number of people on the number of sexual partners they’ve had in their life so far (self reported, but let’s assume they’re perfectly accurate for this question). I wanted to see what variables might predict number of sexual partners. As this is count data, I thought Poisson regression would be best. However, because people are all of different ages, does that mean that the "equal observation time assumption" of Poisson regression is violated? If so, would including age as a variable in the regression correct this?
Thanks!
If the only issue is differing observation durations for different individuals, then using the duration of observation as an offset term is a standard way to proceed in Poisson models. An offset is a predictor that is forced to have a regression coefficient of 1 in the linear predictor, thus directly correcting the total observed counts for the observation period. So in your case you could use the difference between age and "time of beginning sexual career" as an offset.
I suspect, however, that in this particular application there will be a substantial age dependence in the Poisson rate. That will require a more complicated model, as a simple Poisson model assumes a constant underlying rate.
Answered by EdM on November 9, 2021
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