Tal Galili
2010-Jul-11 20:55 UTC
[R] Is there a "Mixed effect model" for regression/classification trees?
Hello all, This is more a statistical question then an R question, but I am sure it will have an R interpretation to it. If I wish to predict an outcome based on some potential features, I could (in some cases) use either regression or regression-tree. However, if my observations are divided to groups (for example by "subject"), I might then want to model that using a random effect for the "subject" and a fixed effect for the other features I wish to model for the prediction. My question is what (if exist) is the parallel of this in regression trees ? Is it simply like adding the "subject" classifier to the tree? or is this leading to a different model scheme all together? (and if so - what is it) Thanks, Tal ----------------Contact Details:------------------------------------------------------- Contact me: Tal.Galili@gmail.com | 972-52-7275845 Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) | www.r-statistics.com (English) ---------------------------------------------------------------------------------------------- [[alternative HTML version deleted]]
Achim Zeileis
2010-Jul-11 23:03 UTC
[R] Is there a "Mixed effect model" for regression/classification trees?
On Sun, 11 Jul 2010, Tal Galili wrote:> Hello all, > > This is more a statistical question then an R question, but I am sure it > will have an R interpretation to it. > > If I wish to predict an outcome based on some potential features, I could > (in some cases) use either regression or regression-tree. > However, if my observations are divided to groups (for example by > "subject"), I might then want to model that using a random effect for the > "subject" and a fixed effect for the other features I wish to model for the > prediction. > My question is what (if exist) is the parallel of this in regression trees ? > Is it simply like adding the "subject" classifier to the tree? or is this > leading to a different model scheme all together? (and if so - what is it)We had thought about doing something in this direction in the model-based recursive partitioning framework (MOB) in the "party" package but never pulled it off. However, I've seen various other ideas at conferences for trees with random intercepts etc. One CRAN package that provides infracstructure for this is "REEMtree" which is probably worth a look. hth, Z> > Thanks, > Tal > > > > > ----------------Contact > Details:------------------------------------------------------- > Contact me: Tal.Galili at gmail.com | 972-52-7275845 > Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) | > www.r-statistics.com (English) > ---------------------------------------------------------------------------------------------- > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >
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