[R] Plotting log transformed predicted values from lme
Michael Dewey
lists at dewey.myzen.co.uk
Thu Aug 10 16:09:53 CEST 2017
On 10/08/2017 13:48, Alina Vodonos Zilberg wrote:
> Thank you Michael,
> Curves for each level of the factor sounds very interesting,
> Do you have a suggestion how to plot them?
>
Make your newdata matrix N times longer where your factor has N levels
and replicate your log(x) down one column and repeat each factor level
118 times.
Then plot the predicted values using lines separately for each subset of
data corresponding to a level of your factor (choosing a different line
type)
> Thank you!
> Alina
>
> *Alina Vodonos Zilberg*
>
>
>
>
> On Thu, Aug 10, 2017 at 7:39 AM, Michael Dewey <lists at dewey.myzen.co.uk
> <mailto:lists at 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]]
>
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