# Re: [R] Plotting log transformed predicted values from lme

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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 <li...@dewey.myzen.co.uk
<mailto: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

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