This is two questions in one, I hope this is OK.
First, I am trying to obtain confidence interval values from an lmer
object from the lme4
package. I've previously used R v 3.4.4 and the models run just fine, and I can find and display the confidence intervals for the mean fit on the plot. I've recently upgraded to R v 3.6.1, and am now getting an error message when using the predict
function. I've shown this below as part of the code
My main question is, how do I calculate the upper and lower confidence limits for a given value? For traditional lm
I would use:
new.dat <- data.frame(variable = ##)
predict(lm_object, newdata = new.dat, interval = 'confidence')
But this doesn't work for lmer
objects.
Here is the data:
TYPE <- c(rep("A", 100), rep("B", 31), rep("C", 18))
MAX<-c(NA,32.6,19.5,23.5,0,17.3,0,31,35.3,23.9,20.8,18.3,10.6,19.4,0,9,14.5,
27.1,0,27.5,21,0,14.7,23.7,17.4,13.7,30.7,25.3,NA,0,16.5,0,NA,18.5,23.9,
8.6,11.9,21.5,0,20.3,10.1,0,20.2,33.6,40.6,21.9,16.6,18.3,0,28.3,36.4,0,
29.4,25.7,24.8,25,0,36.9,19,19.3,27.8,20.4,19.2,0,25.5,26.3,30.6,0,27.8,
5.7,0,21,19.7,15.3,0,16.5,14.5,17.2,31.7,13,21.5,20,32.5,0,6.8,26.2,0,
24.6,21.2,0,32.3,17.3,29.2,43.1,26.2,0,29.5,26.1,36.8,10.9,45.76,17.41,
62.475,0,11.82,57.12,0,41.35,52.935,13.01,0,56.095,60.345,56.645,78.775,
69.565,47.98,15.28,16.46,12.91,0,14.76,29.185,29.26,0,77.72,78.25,0,45.875,
0,40.27,16.43,27.065,45.44,71.38,21.875,0,33.625,45.825,51.79,39.705,27.46,
36.61,44.21,62.38,0,120.295,26.61,0)
STEM_PERCENT<-c(-8.708496564,-8.708496564,-8.708496564,-8.708496564,0,-8.708496564,
0,-8.708496564,-8.708496564,-8.708496564,-8.708496564,-8.708496564,
-8.708496564,-8.708496564,-8.708496564,-8.708496564,-8.708496564,
-8.708496564,0,-8.708496564,-8.708496564,-8.708496564,-8.708496564,
-8.708496564,-8.708496564,-8.708496564,-8.708496564,-8.708496564,
-8.708496564,-8.708496564,-8.708496564,0,-8.708496564,-8.708496564,
-8.708496564,-8.708496564,-8.708496564,-8.708496564,-8.708496564,
-8.708496564,-8.708496564,0,-8.708496564,-8.708496564,-8.708496564,
-8.708496564,-8.708496564,-8.708496564,0,-8.708496564,-8.708496564,0,
-8.708496564,-8.708496564,-8.708496564,-8.708496564,-8.708496564,
-8.708496564,-8.708496564,-8.708496564,-8.708496564,-8.708496564,
-8.708496564,0,-8.708496564,-8.708496564,-8.708496564,0,-8.708496564,
-8.708496564,-8.708496564,-8.708496564,-8.708496564,-8.708496564,0,
-8.708496564,-8.708496564,-8.708496564,-8.708496564,-8.708496564,
-8.708496564,-8.708496564,-8.708496564,-8.708496564,-8.708496564,
-8.708496564,0,-8.708496564,-8.708496564,0,-8.708496564,-8.708496564,
-8.708496564,-8.708496564,-8.708496564,0,-8.708496564,-8.708496564,
-8.708496564,-8.708496564,-7.541459043,0,-7.541459043,0,0,0,0,
-7.541459043,-7.541459043,0,0,-7.541459043,-7.541459043,-7.541459043,
-7.541459043,-7.541459043,0,-7.541459043,8.156584524,-7.541459043,0,
0,8.156584524,-7.541459043,8.156584524,0,-7.541459043,0,-7.541459043,
0,0,0,0,-7.541459043,-15.08291809,0,0,0,-7.541459043,-7.541459043,
-8.156584524,8.156584524,0,0,-16.31316905,0,-16.31316905,0,8.156584524)
val<- data.frame(TYPE, MAX, STEM_PERCENT)
na.strings=c("",NA)
val<-subset(val,MAX!= "NA")
And here is the code which I use to run the mixed effects analysis, which works just fine in R v 3.4.4
library(lme4)
library(merTools)
mod3<-lmer(STEM_PERCENT~1+MAX+(1|TYPE)+(0+MAX|TYPE),data=val)
Here, I get the following error message, which I never received in R v 3.4.4
Warning message:
In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.107451 (tol = 0.002, component 1)
code continues
mod4<-lmer(STEM_PERCENT~1+MAX+(1+MAX|TYPE),data=val) # also produces error not seen before
val2<-expand.grid(MAX=seq(0,120,length=1000),
TYPE=levels(val$TYPE))
val2$STEM_PERCENT<-predict(mod3,newdata=val2)
val3<-data.frame(MAX=seq(0,120,0.1))
val3$STEM_PERCENT<-predict(mod3,newdata=val3,re.form=~0)
CI <- cbind(val2, predictInterval(mod4, val2))
plot(val$MAX,val$STEM_PERCENT,pch=19,col=(1+as.integer((val$TYPE))),
bty="l",cex=0.5,xaxt="n",las=1,ylim=c(-30,10),
xlim=c(0,120),yaxt="n",xlab=NA,ylab=NA)
axis(side=2,tck=-0.02,at=seq(-30,10,10),cex.axis=0.5,
font.axis=1,las=2,mgp=c(0,.5,0),labels=T)
axis(side=1,tck=-0.02,at=seq(0,120,20),
cex.axis=0.5,labels=T,mgp=c(0,-0.1,0))
xv<-seq(0,120,0.01)
typea<-rep("A",length(xv))
yv<-predict(mod3,list(MAX=xv,TYPE=typea),type="response")
Here is where I get the error message in R v 3.6.1, which I don't get in v 3.4.4. The same is true of each instance of yv
Error in rep(0, nobs) : invalid 'times' argument
code continues
lines(xv,yv,col="red",lwd=1.5)
typeb<-rep("B",length(xv))
yv<-predict(mod3,list(MAX=xv,TYPE=typeb),type="response")
lines(xv,yv,col="green",lwd=1.5)
typec<-rep("C",length(xv))
yv<-predict(mod3,list(MAX=xv,TYPE=typec),type="response")
lines(xv,yv,col="blue",lwd=1.5)
lines(val3$MAX,val3$STEM_PERCENT,lwd=2)
ssmin<-smooth.spline(CI$MAX,CI$lwr,df=4)
lines(ssmin,lty=2,col="black",lwd=1)
ssmax<-smooth.spline(CI$MAX,CI$upr,df=4)
lines(ssmax,lty=2,col="black",lwd=1)
Which makes the following plot in R v 3.4.4 with no problems.
I'd like to be able to find upper and low confidence interval values around the mean at a given value of MAX, eg upr
and lwr
limits of the fit
when MAX = 50. It looks like it should be somehwere around -2 and -12 for upr
and lwr
limits respectively. I'd also like to know what's going on with the error messages, which I've not previously received.
Any help and advice gratefully received, thanks
I figured out how to determine CI values. Hopefully others may benefit from the solution. As usual, it was quite simple.
First, round the CIs to 0 dp
CI$MAX<-as.numeric(round(CI$MAX,0))
Then, determine mean upper and lower values at MAX = 50
low<-mean(CI$lwr[which(CI$MAX==50)])
high<-mean(CI$upr[which(CI$MAX==50)])
Add lines to plot to check
abline(v = 50)
abline(h = low)
abline(h = high)
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