[R-sig-ME] Extracting variances from a mer object

[Douglas Bates]

On Wed, Jul 7, 2010 at 4:13 PM, Douglas Bates <bates at stat.wisc.edu> wrote:
> On Wed, Jul 7, 2010 at 4:06 PM, Gang Chen <gangchen6 at gmail.com> wrote:
>> This is a simple question. When fitting a model with lmer, how can I
>> extract all the variances from the output object? For example, with
>> the following analysis, I just want to extract the column of Variance
>> under the Random effects table - those 3 variance numbers: 0.63756 for
>> Subj, 23.03698 for Scan, and 199.50496 for Residual. VarCorr(fm) only
>> gives me the first two. I couldn't find any slots for this purpose
>> from str(fm) either.
>
> ?VarCorr

Sorry, I answered too quickly.  You had checked the result of VarCorr.
 The residual variance is square of the "sc" attribute.

> fm1 <- lmer(Yield ~ 1 + (1|Batch), Dyestuff)
> str(VarCorr(fm1))
List of 1
 $ Batch: num [1, 1] 1764
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr "(Intercept)"
  .. ..$ : chr "(Intercept)"
  ..- attr(*, "stddev")= Named num 42
  .. ..- attr(*, "names")= chr "(Intercept)"
  ..- attr(*, "correlation")= num [1, 1] 1
  .. ..- attr(*, "dimnames")=List of 2
  .. .. ..$ : chr "(Intercept)"
  .. .. ..$ : chr "(Intercept)"
 - attr(*, "sc")= num 49.5
> fm1
Linear mixed model fit by REML
Formula: Yield ~ 1 + (1 | Batch)
   Data: Dyestuff
   AIC   BIC logLik deviance REMLdev
 325.7 329.9 -159.8    327.4   319.7
Random effects:
 Groups   Name        Variance Std.Dev.
 Batch    (Intercept) 1764.0   42.001
 Residual             2451.3   49.510
Number of obs: 30, groups: Batch, 6

Fixed effects:
            Estimate Std. Error t value
(Intercept)  1527.50      19.38   78.81


>>> (fm<-lmer(Rep~(1|Subj)+(1|Scan), data=Model))
>> Linear mixed model fit by REML
>> Formula: Rep ~ (1 | Subj) + (1 | Scan)
>>   Data: Model
>>   AIC   BIC logLik deviance REMLdev
>>  166.4 170.3 -79.18    163.2   158.4
>> Random effects:
>>  Groups   Name        Variance  Std.Dev.
>>  Subj     (Intercept)   0.63756  0.79847
>>  Scan     (Intercept)  23.03698  4.79969
>>  Residual             199.50496 14.12462
>> Number of obs: 20, groups: Subj, 10; Scan, 2
>>
>> Fixed effects:
>>            Estimate Std. Error t value
>> (Intercept)   27.603      4.642   5.946
>>
>> Thanks,
>> Gang
>>
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>>
>