I work in biology and I use mixed-model for my data analysis In a scientific paper, the author wrote: "All continuous exploratory variables were centred on their median value
prior to inclusion in the analysis (Pinheiro & Bates, 2000)."
They refer to the book "Mixed-effects model in S and S-Plus" by Pinheiro et
Bates in 2000.
I feel a bit strange with that paper because I can't find in the book why
they centred the variables on their median.
So I have two question:
First, is it correct to centred the variables on their median in a
mixed-model?
Second, why they do that?
Well I don't recall Pinheiro and Bates saying that variables needed to be centered on their median. It is often the case that the conditioning of the numerical optimization for obtaining parameter estimates is improved if explanatory variables are centered in some way but I don't know of a particular reason for centering on the median. Also, as Bert Gunter pointed out, this statement is about the explanatory variables and not a response variable.
With any statistical model, centering of variables results in a reparameterization of the model and one must keep this in mind when performing statistical tests.
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