Hi everyone,
What is the best way to express the goodness of fit for a model obtained by
generalized least squares (using gls function from nlme package)? I don’t want
to compare this model with other models, so AIC is not a good choice in this
case. Is it right to use the approach proposed by NAKAGAWA, S.; SCHIELZETH, H.
A general and simple method for obtaining R2 from generalized linear
mixed-effects models. Methods in Ecology and Evolution, v. 4, n. 2, p. 133–142,
2013 (rsquared{piecewiseSEM}) to calculate the marginal squared r even if my
model is a simple regression instead a mixed model? For mixed models we get, in
the output, values for marginal and conditional squared r. For models only with
fixed effects we get a value for only one squared r.
Cheers,
Diego Sotto Podadera
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