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

[James Uanhoro]

In addition to Rolf Turner's point, you can get the random effects using
the ranef() function.

ranef(test)$DBID and ranef(test)$familyID should do it.

James


On 07/05/2018 08:40 PM, Rolf Turner wrote:
> 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
>