I am trying to fit a Poisson GLM to count data with several explanatory
variables that are all continuous, except for one that is categorical (0, 1
or 2). (Is categorical the right definition?)

If I standardise the means of the continuous variables using something
like:

data_stan <- cbind(data[, 1:5], apply(X = data[, 6:ncol(data)], MARGIN = 2,
FUN = function(x){(x - mean(x)) / sd(x)}))

will the standardisation cause problems with the categorical variable?

Is there a way to convert the parameter values back for use on
non-standardised data for prediction or will I have to standardise all data
applied to the model afterwards?

Thanks for your help

Austin

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