Dear Thomas and Michael, As Michael knows, there is a default Effect() method in the development version of the effects package on R-Forge. This should work with almost all model objects that produce a single fitted value and that respond to coef(), model.frame(), formula(), and vcov().
This might cover plotting the latent response in clm() or clmm() models but not plots of fitted response-category probabilities such as the effects package can make for models fit by multinom() in the nnet package or polr() in the MASS package. Best, John > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- > project.org] On Behalf Of Michael Friendly > Sent: Tuesday, November 05, 2013 10:08 AM > To: thomas; r-help@r-project.org > Cc: John Fox > Subject: Re: [R] How to plot results of clmm()? > > On 11/4/2013 9:13 AM, thomas wrote: > > Dear list, > > > > I'd like to create a visual plot of a clmm() I've fitted using the > > 'ordinal' package in R. It's possible to do this with a glm() by > using > > the 'effects' package. For example: > > > > library(effects) > > data(BEPS) > > mod <- lm(political.knowledge ~ age + gender + vote, data=BEPS) > > eff <- effect("age", mod, default.levels=100) > > plot(eff, colors=c("black", "red")) > > > > Produces: http://i.stack.imgur.com/elo4p.png > > > > The 'effects' package does not support clmm: > > > > mod <- clmm(as.factor(political.knowledge) ~ age + gender + > > (1|vote), data=BEPS) > > eff <- effect("age", mod, default.levels=100) > > > Error in UseMethod("effect", mod) : > > no applicable method for 'effect' applied to an object of class > "clmm" > > > > How would I go about doing this? I can't find any examples with clm() > or > > clmm() online. Any suggestions would be much appreciated. > > > > You're right that clm() and clmm() models are not supported by the > effects package. In principle, this would not be too difficult to add, > *if* the ordinal package contained the standard collection of methods > for > 'clm' and 'clmm' objects --- coef(), vcov(), and importantly, > predict(). > Unfortunately, there is no predict method, and clmm objects don't > inherit from anything else: > > > methods(class="clmm") > [1] anova.clmm* condVar.clmm* extractAIC.clmm* logLik.clmm* > [5] nobs.clmm* print.clmm* ranef.clmm summary.clmm* > [9] VarCorr.clmm vcov.clmm* > > class(modc) > [1] "clmm" > > > > If there were, you could simply do what effects does yourself -- > obtain predicted values (and CIs) over a grid of values, and plot them, > > xlevels <- expand.grid(list(age=seq(20,90,10), > gender=levels(BEPS$gender), vote=levels(BEPS$vote))) > > You can, of course, obtain all the fitted values, and plot those, > but that lacks the simplicity of effect plots in averaging over factors > not shown in a given plot. > > library(ordinal) > modc <- clmm(as.factor(political.knowledge) ~ age + gender + > (1|vote), data=BEPS) > > BEPS$fitted <- fitted(modc) > plot(fitted~age, data=BEPS, col=c("red", "blue")[gender]) > > > > -- > Michael Friendly Email: friendly AT yorku DOT ca > Professor, Psychology Dept. & Chair, Quantitative Methods > York University Voice: 416 736-2100 x66249 Fax: 416 736-5814 > 4700 Keele Street Web: http://www.datavis.ca > Toronto, ONT M3J 1P3 CANADA > > ______________________________________________ > 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. ______________________________________________ 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.
