Drawing a quadratic function in mixed effect model - r

Question

It's a bit of a long question so thanks for bearing with me.
Here's my data
https://www.dropbox.com/s/jo22d68a8vxwg63/data.csv?dl=0
I constructed a mixed effect model
library(lme4)
mod <- lmer(sqrt(y) ~ x1 + I(x1^2) + x2 + I(x2^2) + x3 + I(x3^2) + x4 + I(x4^2) + x5 + I(x5^2) +
x6 + I(x6^2) + x7 + I(x7^2) + x8 + I(x8^2) + (1|loc) + (1|year), data = data)
All the predictors are standardised and I am interested in knowing how does y changes with changes in x5while keeping other variables at their mean values (equal to 0 since all the variables are standardised).
This is how I do it.
# make all predictors except x5 equal to zero
data$x1<-0
data$x2<-0
data$x3<-0
data$x4<-0
data$x6<-0
data$x7<-0
data$x8<-0
# Use the predict function
library(merTools)
fitted <- predictInterval(merMod = mod, newdata = data, level = 0.95, n.sims = 1000,stat = "median",include.resid.var = TRUE)
Now I want to plot the fitted as a quadratic function of x5. I do this:
i<-order(data$x5)
plot(data$x5[i],fitted$fit[i],type="l")
I expected this to produce a plot of y as a quadratic function of x5. But As you can see, I get the following plot which does not have any quadratic curve. Can anyone tell me what I am doing wrong here?

Answer 1

I'm not sure where predictInterval comes from, but you can do this with predict. The trick is just to make sure you set your random effects to 0. Here's how you can do that
newdata <- data
newdata[,paste0("x", setdiff(1:8,5))] <- 0
y <- predict(mod, newdata=newdata, re.form=NA)
plot(data$x5, y)
The re.form=NA part drops out the random effect