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Hi, I am attempting to set the confidence limits on a ls means plot as follows: mult<-glht(lm(effectModel, data=statdata, na.action = na.omit), linfct=mcp(mainEffect="Means")) meanPlot <- sub(".html", "meanplot.jpg", htmlFile) jpeg(meanPlot) plot(mult, main=NA, xlab=unlist(strsplit(Args[4],"~"))[1]) This produces 95% CIs by default but I would like to produce 99% CIs - How do I do this? Thanks, Robin -- View t...

...2j]x[2ij] + R[ij] Now I start modelling step by step and I would appreciate any corrections if I got something wrong. An empty model: e.model <- lme(y~1,random=~1|G) With one explanatory variable: fm1.lme <- lme(y~x1,random = ~1|G) With two exp. variables, assuming that there are only maineffects for my variables: fm2.lme <- lme(y ~ x1 + x2+ ... + x7, random = ~1|G) The same, adding an interaction effect: fm3.lme <- lme(y~x1*x2,random=~1|G) This is how far i got. Now i would like to add the z-variable into the model. How do i do this ? Yours sincerly Felix Eschenburg