I am trying to predict the daily amount of waste per person produced in the fishery sector. We surveyed fishing boats at the end of their fishing trip and the variables I have are duration of trip (days), number of fishers, waste category and waste weight (g), boat ID.
For each fishing trip I calculated grams of waste per person per day, i.e. daily waste per capita.
To predict daily waste per capita, I am using a Gaussian mixed effect model with log(waste per capita) as response variable (I transformed it cause it was not normally distributed – and I'm not sure it's correct to do so). Explanatory variable is waste category and boat ID is a random effect.
I use the predict function to estimate daily waste per capita for each category and then back transformed it with exp(...).
My question is: is it correct to transform daily weight per capita to fit a Gaussian model?