[R-sig-ME] Unidentifiable model in lmer
Jake Westfall
jake987722 at hotmail.com
Fri Sep 18 00:53:14 CEST 2015
I believe this is a problem in lmerTest, not in lme4. I seem to recall running into a problem like this myself in the past, where lmerTest claimed that a model was not identifiable when I called summary() on it, even though I was pretty confident the model was fine and lmer() did not complain at all when fitting the model. (I don't think I ever figured out what was making it happen.)
Jake
> To: r-sig-mixed-models at r-project.org
> From: taka.6765 at gmail.com
> Date: Thu, 17 Sep 2015 17:52:56 -0400
> Subject: [R-sig-ME] Unidentifiable model in lmer
>
> Hi everyone,
>
> I have been working on a linear mixed effect model by using lmer()
> function, but I got an error saying that the fitted model is not
> identifiable.
>
> The data set includes the following variables:
> y = a numeric variable
> factorA = a 3-level categorical variable
> factorB = a 2-level categorical variable
> subjectID = subject id number. 2 measurements of y for each subject
>
> R code and output are as follows:
> > (result <- lmer(y ~ factorA + factorB + factorA*factorB +
> (1|subjectID)))
> Linear mixed model fit by REML ['merModLmerTest']
> Formula: y ~ factorA + factorB + factorA * factorB + (1 | subjectID)
> REML criterion at convergence: 1928.966
> Random effects:
> Groups Name Std.Dev.
> subjectID (Intercept) 4711
> Residual 7688
> Number of obs: 97, groups: subjectID, 51
> Fixed Effects:
> (Intercept) factorA1 factorA2 factorB1
> factorA1:factorB1 factorA2:factorB1
> 62411 -2700 -1124
> -1037 1279 2482
> > summary(result)
> Model is not identifiable...
> summary from lme4 is returned
> some computational error has occurred in lmerTest
> Linear mixed model fit by REML ['lmerMod']
> Formula: y ~ factorA + factorB + factorA * factorB + (1 | subjectID)
>
> REML criterion at convergence: 1929
>
> Scaled residuals:
> Min 1Q Median 3Q Max
> -1.93423 -0.62611 0.01837 0.48887 2.73380
>
> Random effects:
> Groups Name Variance Std.Dev.
> subjectID (Intercept) 22194074 4711
> Residual 59108495 7688
> Number of obs: 97, groups: subjectID, 51
>
> Fixed effects:
> Estimate Std. Error t value
> (Intercept) 62411 2065 30.227
> factorA1 -2700 3238 -0.834
> factorA2 -1124 3008 -0.374
> factorB1 -1037 2512 -0.413
> factorA1:factorB1 1279 4013 0.319
> factorA2:factorB1 2482 3642 0.681
>
> Correlation of Fixed Effects:
> (Intr) fctrA1 fctrA2 fctrB1 fA1:B1
> factorA1 -0.638
> factorA2 -0.687 0.438
> factorB1 -0.608 0.388 0.418
> fctrA1:fcB1 0.381 -0.601 -0.262 -0.626
> fctrA2:fcB1 0.420 -0.268 -0.606 -0.690 0.432
> >
>
> Could anyone give me some idea of why this unidentifiability problem
> happens and how to fix it?
> Any help would be appreciated.
>
> Best regards,
> Takahiro
>
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