Great lists, I always find them useful, thank you to
everyone who contributes to them.
My question is regarding non-integer values from some data I
collected on parrots when using the poisson GLM. I observed the parrots on a
daily basis to see if they were affected by tourist presence. My key predictors
are tourist noise (averaged over a day period so decimal value, square root to
adjust for skew), tourist number (the
number of tourists at a site, square root), and the number of boats passing the
site in a day (log). These are compared with predictors: total number of birds
(count data, square root), average time devoted to foraging at site (log),
species
richness (sqrt), and the number of flushes per day. Apart from the last one
they are all non-integer values. When I run a glm for example:
parrots <- glm(tnoise_sqrt ~ lengthfeeding_log, family poisson)
summary(parrots)
There are warnings which are “27: In dpois(y, mu, log TRUE) : non-integer x =
1.889822” I was advised to use the offset() function
however this does not seem to correct the problem and I find the code confusing.
What GLM approach should I be using for multiple non-integer predictors and
non-integer responses? Does my GLM approach seem appropriate?
Thank you for taking the time to consider this.
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