# Plotting log transformed predicted values from lme

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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.
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## Re: Plotting log transformed predicted values from lme

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## Re: Plotting log transformed predicted values from lme

 In reply to this post by Duststorm In the rockchalk package, I have a function called newdata that will help with this. Plenty of examples. Probably my predictOmatic function will just work. Motivation is in the vignette. Paul Johnson University of Kansas On Aug 9, 2017 11:23 AM, "Alina Vodonos Zilberg" <[hidden email]> 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. >         [[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.