Thanks Duncan and David for opening my eyes :-). It took quite a while but I think I learned a lot about lm today. I used your advice to produce "added variable plots" as mentioned here [1], [2]. I would bet someone did it in R already (may leverage.plot in car) but it was worth doing it myself.
Kind regards, Karsten. [1] http://www.minitab.com/support/documentation/answers/AVPlots.pdf [2] http://www.mathworks.com/access/helpdesk/help/toolbox/stats/addedvarplot.html plotAddedVar.lm <- function( linModel, termName, main="", xlab=paste(termName, " | andere"), ylab=paste(colnames(linModel$model)[1], " | andere"), cex=0.7, ...) { oldpar <- par(no.readonly = TRUE); on.exit(par(oldpar)) par(mar=c(3,4,0.4,0)+0.1, las=1, cex=cex) yData = residuals(update(linModel, substitute(. ~ . - x, list(x=as.name(termName))))) xData = residuals(update(linModel, substitute(x ~ . - x, list(x=as.name(termName))))) plot(xData, yData, main=main, xlab="", ylab="") mtext(side=2, text=ylab, line=3, las=0, cex=cex) mtext(side=1, text=xlab, line=2, las=0, cex=cex) abline(h=0) abline(a=0, b=coefficients(linModel)[termName], col="blue") } plotAddedVar <- function(linModel,...) UseMethod("plotAddedVar") ______________________________________________ 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.
