Thank you Michael, Curves for each level of the factor sounds very interesting, Do you have a suggestion how to plot them?
Thank you! Alina *Alina Vodonos Zilberg* On Thu, Aug 10, 2017 at 7:39 AM, Michael Dewey <li...@dewey.myzen.co.uk> wrote: > Dear Alina > > If I understand you correctly you cannot just have a single predicted > curve but one for each level of your factor. > > > On 09/08/2017 16:24, Alina Vodonos Zilberg wrote: > >> Hi, >> >> I am performing meta-regression using linear mixed-effect model with the >> lme() function that has two fixed effect variables;one as a log >> transformed variable (x) and one as factor (y) variable, and two nested >> random intercept terms. >> >> I want to save the predicted values from that model and show the log curve >> in a plot ; predicted~log(x) >> >> mod<-lme(B~log(x)+as.factor(y), random=~1|cohort/Study, >> weights=varFixed(~I(SE^2)), na.action=na.omit, data=subset(meta), >> control = lmeControl(sigma = 1, apVar = FALSE)) >> summary(mod) >> >> newdat <- data.frame(x=seq(min(meta$x), max(meta$x),,118)) # I have 118 >> observations. #How do I add the factor variable to my newdat? >> newdat$pred <- predict(mod, newdat,level = 0,type="response") >> >> plot(B ~ x, data=meta) >> lines(B ~ x, data=newdat) >> >> Can you please assist me ? >> >> Thank you! >> >> Alina >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posti >> ng-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> >> --- >> This email has been checked for viruses by AVG. >> http://www.avg.com >> >> >> > -- > Michael > http://www.dewey.myzen.co.uk/home.html > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
