On Wed, 2009-11-25 at 16:55 -0800, ychu066 wrote: > How should I analysis it in R ???? all the resposes variables are ordinal > from 0 to 10. and the explanatory variable is a factor ...
You give very little to go on (please read the posting guide for future reference), but: If you want to analyse all the responses at once: A VGLM might be useful; see the VGAM package on CRAN and the author's (Thomas Yee) web site for lots of useful information. A constrained ordination might also be useful. cca() in package vegan, or capscale() (also in vegan) with a suitable dissimilarity for ordinal data (see daisy() in package cluster for such dissimilarities). If you want to model the 200 responses separately (i.e. 200 models) then polr() in package MASS or lrm() in package rms would be places to start. HTH G -- %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% Dr. Gavin Simpson [t] +44 (0)20 7679 0522 ECRC, UCL Geography, [f] +44 (0)20 7679 0565 Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/ UK. WC1E 6BT. [w] http://www.freshwaters.org.uk %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% ______________________________________________ R-help@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.
