Thanks a lot for your advice. What do you mean with "the proportional-odds assumption may not hold"? Does this solution with "polr" always works? Or what's important to take into account?
Regards Thomas >Dear Thomas, > >One approach to an ordinal response variable is the proportional-odds model, >implemented in the MASS package as polr(). The proportional-odds >assumption >may not hold, however. > >I hope this helps, > John > > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of > [EMAIL PROTECTED] > Sent: Wednesday, May 05, 2004 7:45 AM > To: [EMAIL PROTECTED] > Subject: [R] Analysis of ordinal categorical data > > Hi > > I would like to analyse an ordinal categorical variable. I > know how I can analyse a nominal categorical variable (with > multinom or if there are only two levels with glm). > > Does somebody know which command I need in R to analyse an > ordinal categorical variable? > > I want to describe the variable y with the variables x1,x2,x3 > and x4. So my model looks like: y ~ x1+x2+x3+x4. > > y: ordinal factor variable with levels (never, rare, bychance, often). > > Thanks a lot in advance > Thomas > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
