what does order() stand for in an lme formula?
"Harry Athanassiou" <hathanassiou at automatedcell.com> writes:
I'm a beginner in R, and trying to fit linear models with different
intercepts per group, of the type y ~ A*x1 + B, where x1 is a numerical
variable. I cannot understand whether I should use
y1 ~ x1 +1
or
y1 ~ order(x1) + 1
Although in the toy example included it makes a small difference, in models
with many groups the models without order() converge slower if at all!
Er? What gave you the idea of using order in the first place? To the best of my knowledge, order(x) is also in this context just a function, which for the nth observation returns the position of the nth largest observation in x. This is not likely to make sense as a predictor in a model.
O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907