[R-sig-ME] singular convergence with lmer()
djmuser at gmail.com
Mon Jul 9 01:09:22 CEST 2012
FWIW, I get the same result using
On Sun, Jul 8, 2012 at 2:58 PM, Baldwin, Jim -FS <jbaldwin at fs.fed.us> wrote:
> I wonder if it is a version issue. Using the data at forums.cirad.fr/logiciel-R/viewtopic.php?t=5071 I get the following (which matches what SAS produces):
> 'data.frame': 192 obs. of 3 variables:
> $ Operator: Factor w/ 8 levels "A","B","C","D",..: 1 1 1 1 1 1 1 1 1 1 ...
> $ Part : Factor w/ 12 levels "1","2","3","4",..: 1 1 2 2 3 3 4 4 5 5 ...
> $ y : num 0.724 0.699 1.554 1.535 1.786 ...
> Linear mixed model fit by REML
> Formula: y ~ (1 | Operator) + (1 | Part) + (1 | Part:Operator)
> Data: dat
> AIC BIC logLik deviance REMLdev
> -619.7 -603.4 314.9 -630.3 -629.7
> Random effects:
> Groups Name Variance Std.Dev.
> Part:Operator (Intercept) 0.00081854 0.028610
> Part (Intercept) 1.06721993 1.033063
> Operator (Intercept) 0.00031226 0.017671
> Residual 0.00063295 0.025159
> Number of obs: 192, groups: Part:Operator, 96; Part, 12; Operator, 8
> Fixed effects:
> Estimate Std. Error t value
> (Intercept) 2.7171 0.2983 9.109
> I'm using R 1.15.0 32-bit on Windows XP and Package lme4 version 0.999375-42.
> Jim Baldwin
> Pacific Southwest Research Station
> USDA Forest Service
> Albany, California
> -----Original Message-----
> From: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf Of Joshua Wiley
> Sent: Sunday, July 08, 2012 1:52 PM
> To: laurent stephane
> Cc: r-sig-mixed-models at r-project.org
> Subject: Re: [R-sig-ME] singular convergence with lmer()
> Notice that the variance of one of your random effects is estimated at 0. I suspect that this is the source of the singular convergence.
> IIRC proc mixed (which is what I assume you are using in SAS) uses a somewhat different approach to to estimate the random effects than does lme4.
> Although it seems to work for Reinhold, again some of the variances are vanishingly small, which seems to me like it may suggest some of the effects are borderline on 0 and perhaps slightly different estimation methods either get "really small" or simply "0" and if 0, you get a warning. I would also consider simplifying your model (although likelihood ratio tests seem to suggest a significant decrement in the likelihood fixing the variance at 0).
> On Thu, Jul 5, 2012 at 1:01 AM, laurent stephane <laurent_step at yahoo.fr> wrote:
>> Dear all,
>> Using the latest CRAN version of lme4 I get the following warning from lmer() :
>> Warning message:
>> In mer_finalize(ans) : singular convergence (7)
>> My model is not complicated and it works fine with SAS (if you are
>> interested in the details of my model see
>> forums.cirad.fr/logiciel-R/viewtopic.php?t=5071 )
>> What argument could I change in lmer() to overcome this warning ?
>> Kind regards,
>> [[alternative HTML version deleted]]
>> R-sig-mixed-models at r-project.org mailing list
> Joshua Wiley
> Ph.D. Student, Health Psychology
> Programmer Analyst II, Statistical Consulting Group University of California, Los Angeles https://joshuawiley.com/
> R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
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