Hello, I've recently started using the rms package to fit some continuation ratio models using cr.setup. The package runs beautifully and I'm getting good fits with my data, however, I'm having trouble getting plots of the predicted mean values of y in relation to predictor variables with confidence intervals. Specifically, when I use a function such as L <- predict(ord.cr, se.fit=TRUE), I get an error command that states: Error in X %*% cov : non-conformable arguments. For reference, my model statement (and as I mentioned above, it fits nicely to my data) and follow-up code looks something like this :
ord.cr <- lrm(y ~ cohort + a + b, x=TRUE, na.action=na.delete) L <- predict(ord.cr, se.fit=TRUE) plogis(with(L, linear.predictors + 1.96*cbind(-se.fit,se.fit))) predict(ord.cr, type="fitted.ind") predict(ord.cr, all.data1.stand, type="fitted") predict(ord.cr, all.data1.stand, type="fitted.ind") predict(ord.cr, all.data1.stand, type='mean', codes=TRUE) m <- Mean(ord.cr, codes=TRUE) lp <- predict(ord.cr, all.data1.stand) m(lp) ddist <- datadist(a, b) options(datadist='ddist') m x11() plot(Predict(ord.1, a, fun=m), ylim=(0:14), xlab='a', ylab='Predicted mean y') options(datadist=NULL) Is it possible to use predict to produce such a plot and if not, what is the best approach? Thanks for any and all assistance. Adam -- View this message in context: http://r.789695.n4.nabble.com/cr-setup-predict-with-se-fit-tp3461236p3461236.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
