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

Rolf Turner r@turner @ending from @uckl@nd@@c@nz
Fri Jul 6 02:40:03 CEST 2018


On 06/07/18 02:10, Burcu Darst via R-sig-mixed-models wrote:
> 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!


I am no expert --- and younger and wiser heads may correct me --- but it 
is my understanding that "types" of residuals are relevant only in the 
context of *generalised* linear models (mixed or "straight").  For 
linear models (mixed or "straight") a residual is a residual is a 
residual.  (And a caterpillar is a tractor. :-) )

cheers,

Rolf Turner

-- 
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276



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