CODEWITHSUNDEEP
rplotlme4confidence-interval
Luis M. García
Luis M. García

Reputation: 143

Extract the confidence intervals of lmer random effects; plotted with dotplot(ranef())

I´m trying to extract the confidence intervals and the intercept values that are plotted with dotplot(ranef()). How can I do this?

attach(sleepstudy)
library(lme4)
fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
lattice::dotplot(ranef(fm1, condVar=TRUE))

enter image description here

I tried exploring the list object fm1 but could not fiund the CI.

Upvotes: 5

Views: 2446

Answers (1)

Ben Bolker
Ben Bolker

Reputation: 226182

rr <- ranef(fm1)  ## condVar = TRUE has been the default for a while

With as.data.frame: gives the conditional mode and SD, from which you can calculate the intervals (technically, these are not "confidence intervals" because the values of the BLUPs/conditional modes are not parameters ...)

dd <- as.data.frame(rr)
transform(dd, lwr = condval - 1.96*condsd, upr = condval + 1.96*condsd)

Or with broom.mixed::tidy:

broom.mixed::tidy(m1, effects = "ran_vals", conf.int = TRUE)

broom.mixed::tidy() uses as.data.frame.ranef.mer() (the method called by as.data.frame) internally: this function takes the rather complicated data structure described in ?lme4::ranef and extracts the conditional modes and standard deviations in a more user-friendly format:

If ‘condVar’ is ‘TRUE’ the ‘"postVar"’ attribute is an array of dimension j by j by k (or a list of such arrays). The kth face of this array is a positive definite symmetric j by j matrix. If there is only one grouping factor in the model the variance-covariance matrix for the entire random effects vector, conditional on the estimates of the model parameters and on the data, will be block diagonal; this j by j matrix is the kth diagonal block. With multiple grouping factors the faces of the ‘"postVar"’ attributes are still the diagonal blocks of this conditional variance-covariance matrix but the matrix itself is no longer block diagonal.

In this particular case, here's what you need to do to replicate the condsd column of as.data.frame():

## get the 'postVar' attribute of the first (and only) RE term
aa <- attr(rr$Subject, "postVar")
## for each slice of the array, extract the diagonal;
##  transpose and drop dimensions;
##  take the square root
sqrt(c(t(apply(aa, 3, diag))))

Upvotes: 6

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