On Tue, 22 Jan 2013, Jason Musil wrote:
DeaR all,I am using mob() for model based partitioning, with a dichotomous variable (participant's correct/incorrect response to a test item) regressed onto a continuous predictor related to a given property of the test item. Although this variable is continuous, the value of this variable for many items in this particular analysis is 0. The partitioning criterion is self-reported ability in a related area.mob1 <- mob(correct ~ circular.mean | srp.dimension, control=mob_control(alpha=.001), model=glinearModel, family=binomial() )plot(mob1)Error in cut.default(x, breaks = breaks, include.lowest = TRUE) : 'breaks' are not uniqueThe same persists if I specify either a desired number of breaks, or explicit breakpoints (e.g. breaks=3 or breaks=c(-0.1,0.1,0.5)). I guess this is to do with the funny distribution of the predictor variable, but I'm not sure what to do about it.
Jason, you can't pass the "breaks" argument to the plot method directly but need to pass it on to the panel function drawing the terminal panels. As an example consider
example("mob")
plot(fmPID)
plot(fmPID, tp_args = list(breaks = c(0, 100, 120, 200)))
Hope that fixes your problem.
Best,
Z
Many thanks and apologies if this doesn't fit the mailing list---it is my first posting! Jason Musil ______________________________________________ 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.
