What do you think?
When reporting data in an article, a usual way is to show the mean values +/- the standard errors in a table. For Example, when you measure Abundance of pigeons in parks of five different cities, with each city having 30 parks. You would condense the data and show the MEAN +/- SE for each of the five towns.
However, if you analyse your data using GLM with i.e. poisson or negative binomial distribution. And furthermore you do not only analyse Town as explanator but also covariables, like..whatever, Rainfall, Temperature, amounts of trees in the park, etc. Is it still justifiable to condense the data by showing MEAN and SE values for the towns, or would you expect Estimators +/- SE from the GLMs in the reported data table? Because for me it seems that the MEAN is not very representative when the data are not normally distributed. Or do I mix up two different things? Reporting Data on the one hand and reporting Analysis Results on the other?