[R-sig-ME] Types of residuals in lme4

[Burcu Darst]

Dear All,

I am using lme4 to get residuals from a model that has two random intercepts, as shown below:

test = lmer(continuousOutcome ~ age + sex + (1|DBID) + (1|familyID), data, na.action = na.exclude)


I’ve tried extracting all of the following types of residuals, but the only differences I observe between these approaches are due to scaling; i.e., residuals do not differ by residual type.

resids = as.data.table(residuals(test,type = "pearson", scaled = TRUE))
resids = as.data.table(residuals(test,type = "working", scaled = TRUE))
resids = as.data.table(residuals(test,type = "response", scaled = TRUE))
resids = as.data.table(residuals(test,type = "deviance", scaled = TRUE))
resids = as.data.table(residuals(test,type = "pearson"))
resids = as.data.table(residuals(test,type = "working"))
resids = as.data.table(residuals(test,type = "response"))
resids = as.data.table(residuals(test,type = "deviance"))


Is this an expected result when using lme4 to obtain residuals from mixed models? I want to ensure that the residuals I am obtaining are observation level (which they appear to be) and that they account for the two random intercepts (which I believe they do, since they differ if I exclude one of the random intercepts). Also, is it possible to get higher level residuals from lme4, such as individual or family level residuals (which are the two random intercepts included in my model)? 

I would greatly appreciate any help!

Best,
Burcu