I have count data for events measured within each of multiple individuals. However, the amount of time over which each individual was observed varies. Normally, if the counts were obtained over equal amounts of time, I'd do something like:
fit = lmer( data = my_data , formula = count ~ (1|individual) , family = poisson )
However, I'm not sure how to handle things when the amount of time is unequal. If I simply divide each individual's count by the amount of time the were observed, this yields a counts-per-minute measure, but the poisson family does not like non-integer values in the dv. Any suggestions?