What you suggest is certainly meaningful (that is the hypothesis tested makes sense), but raises an issue of simultaneous inference. There are simultaneous comparison procedures for dealing with this kind of problem. See, for example, the multcomp package.
John
At 12:05 PM 2/18/2003 -0200, you wrote:
Is it meaningful to run 2 different sets of contrasts on a model , or is there some redundancy somewhere ? For example,I have a model : tcons ~ groupwhere group is a factor with 3 levels ( A, B, C) I first run the model with the default contrasts (treatment), so I tested (A vs B) and (A vs C); but is it meaningful to also carry on a 2nd analysis with an other set of contrasts, to test B vs C ? ie c(0,-1,1) , in fit.contrasts gregmisc notation. I'v heard that the first set of contrast ( ie treatment default in the example) extracts all the "information" in the model, and that a second analysis with an other set of contrasts was not meaningful.
----------------------------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario, Canada L8S 4M4 email: [EMAIL PROTECTED] phone: 905-525-9140x23604 web: www.socsci.mcmaster.ca/jfox ----------------------------------------------------- ______________________________________________ [EMAIL PROTECTED] mailing list http://www.stat.math.ethz.ch/mailman/listinfo/r-help
