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As for the PLS models, mean centered first derivative (Sav-Gol, polynomial order 2, window size 11) spectra gave the best results.
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To ensure that each model does not simply describe the mean expression level of a target gene, we mean centered all the expression profiles.
For convenience, we reparameterize the multiplicative model by mean-centering the genotypes, where is the genotype mean and is the new baseline parameter.
To focus estimates of associations at the subject level, we adjusted for between-community and between-phase exposure effects as proposed by Janes et al. (2008) by using exposures that were mean-centered across community and phase [see Supplemental Material, Regression Model, Mean Centering Method (doi 10.1289/ehp.0901407)].
Prior to use in the modeling all cross-terms were mean-centered.
The spectra were mean-centered before the PLS-DA modeling.
Each model was built using transformed spectral data that had been mean-centered.
Age is mean-centered.
The data were also mean-centered.
All continuous independent variables in the model were grand mean centered.
When non-standardized income variables were included into the models, they were grand mean centered.
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