# Plotting log transformed predicted values from lme Classic List Threaded 5 messages Open this post in threaded view
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## Plotting log transformed predicted values from lme

 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]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Plotting log transformed predicted values from lme

 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]] > > ______________________________________________ > [hidden email] 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. > > --- > This email has been checked for viruses by AVG. > http://www.avg.com> > -- Michael http://www.dewey.myzen.co.uk/home.html______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Plotting log transformed predicted values from lme

 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 <[hidden email]> 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]] >> >> ______________________________________________ >> [hidden email] 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]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.