Re: [R] convergence error code in mixed effects models

From: Mark Difford <mark_difford_at_yahoo.co.uk>
Date: Fri, 14 Dec 2007 19:26:21 -0800 (PST)

Hi Ilona,

>> Is there a solution for this problem?

If there is, then Professor Bates (the gentleman who replied to your question) will have tried to find it, and fix it, for you.

Professor Bates wrote/co-wrote the software package (nlme) you are using. And while I have nothing against Crawley's book, you are usually much better off going to primary sources first, to solve this kind of problem (which, of course you have done, though may not have been aware of it ;)

Mixed-Effects Models in S and S-PLUS, by: Pinheiro, José, Bates, Douglas http://www.springer.com/west/home/statistics/computational?SGWID=4-10130-22-2102822-0

Hope this speeds you on your way...

Regards, Mark.

Ilona Leyer wrote:
>
>
> Here an simple example:
>
> rep treat heightfra leaffra leafvim week
> ID1 pHf 1.54 4 4 4
> ID2 pHf 1.49 4 4 4
> ID3 pHf 1.57 4 5 4
> ID4 pHf 1.48 4 4 4
> ID5 pHf 1.57 4 4 4
> ID6 pHs 1.29 4 5 4
> ID7 pHs 0.97 4 5 4
> ID8 pHs 2.06 4 4 4
> ID9 pHs 0.88 4 4 4
> ID10 pHs 1.47 4 4 4
> ID1 pHf 3.53 5 6 6
> ID2 pHf 4.08 6 6 6
> ID3 pHf 3.89 6 6 6
> ID4 pHf 3.78 5 6 6
> ID5 pHf 3.92 6 6 6
> ID6 pHs 2.76 5 5 6
> ID7 pHs 3.31 6 7 6
> ID8 pHs 4.46 6 7 6
> ID9 pHs 2.19 5 5 6
> ID10 pHs 3.83 5 5 6
> ID1 pHf 5.07 7 7 9
> ID2 pHf 6.42 7 8 9
> ID3 pHf 5.43 6 8 9
> ID4 pHf 6.83 6 8 9
> ID5 pHf 6.26 6 8 9
> ID6 pHs 4.57 6 9 9
> ID7 pHs 5.05 6 7 9
> ID8 pHs 6.27 6 8 9
> ID9 pHs 3.37 5 7 9
> ID10 pHs 5.38 6 8 9
> ID1 pHf 5.58 7 9 12
> ID2 pHf 7.43 8 9 12
> ID3 pHf 6.18 8 10 12
> ID4 pHf 6.91 7 10 12
> ID5 pHf 6.78 7 10 12
> ID6 pHs 4.99 6 13 12
> ID7 pHs 5.50 7 8 12
> ID8 pHs 6.56 7 10 12
> ID9 pHs 3.72 6 10 12
> ID10 pHs 5.94 6 10 12
>
>
> I used the procedure described in Crawley´s new R
> Book.
> For two of the tree response variables
> (heightfra,leaffra) it doesn´t work, while it worked
> with leafvim (but in another R session, yesterday,
> leaffra worked as well...).
>
> Here the commands:
>

>> attach(test)
>> names(test)

> [1] "week" "rep" "treat" "heightfra"
> "leaffra" "leafvim"
>> library(nlme)
>>

> test<-groupedData(heightfra~week|rep,outer=~treat,test)
>> model1<-lme(heightfra~treat,random=~week|rep)

> Error in lme.formula(heightfra ~ treat, random = ~week
> | rep) :
> nlminb problem, convergence error code = 1;
> message = iteration limit reached without convergence
> (9)
>
>>

> test<-groupedData(leaffra~week|rep,outer=~treat,test)
>> model2<-lme(leaffra~treat,random=~week|rep)

> Error in lme.formula(leaffra ~ treat, random = ~week |
> rep) :
> nlminb problem, convergence error code = 1;
> message = iteration limit reached without convergence
> (9)
>
>>

> test<-groupedData(leafvim~week|rep,outer=~treat,test)
>> model3<-lme(leafvim~treat,random=~week|rep)
>> summary(model)

> Error in summary(model) : object "model" not found
>> summary(model3)

> Linear mixed-effects model fit by REML
> Data: NULL
> AIC BIC logLik
> 129.6743 139.4999 -58.83717
>
> Random effects:
> Formula: ~week | rep
> Structure: General positive-definite, Log-Cholesky
> parametrization
> StdDev Corr
> (Intercept) 4.4110478 (Intr)
> week 0.7057311 -0.999
> Residual 0.5976143
>
> Fixed effects: leafvim ~ treat
> Value Std.Error DF t-value p-value
> (Intercept) 5.924659 0.1653596 30 35.82893 0.0000
> treatpHs 0.063704 0.2338538 8 0.27241 0.7922
> Correlation:
> (Intr)
> treatpHs -0.707
>
> Standardized Within-Group Residuals:
> Min Q1 Med Q3
> Max
> -1.34714254 -0.53042878 -0.01769195 0.40644540
> 2.29301560
>
> Number of Observations: 40
> Number of Groups: 10
>
> Is there a solution for this problem?
>
> Thanks!!!
>
> Ilona
>
> --- Douglas Bates <bates_at_stat.wisc.edu> schrieb:
>
>> On Dec 13, 2007 4:15 PM, Ilona Leyer
>> <ileyer_at_yahoo.de> wrote:
>> > Dear All,
>> > I want to analyse treatment effects with time
>> series
>> > data:  I measured e.g. leaf number (five replicate
>> > plants) in relation to two soil pH - after 2,4,6,8
>> > weeks. I used mixed effects models, but some
>> analyses
>> > didn´t work. It seems for me as if this is a
>> randomly
>> > occurring problem since sometimes the same model
>> works
>> > sometimes not.
>> >
>> > An example:
>> > > names(test)
>> > [1] "rep"    "treat"  "leaf"   "week"
>> > > library (lattice)
>> > > library (nlme)
>> > >
>> test<-groupedData(leaf~week|rep,outer=~treat,test)
>> > > model<-lme(leaf~treat,random=~leaf|rep)
>> > Error in lme.formula(leaf~ treat, random =
>> ~week|rep)
>> 
>> Really!? You gave lme a model with random = ~ leaf |
>> rep (and no data
>> specification) and it tried to fit a model with
>> random = ~ week | rep?
>> Are you sure that is an exact transcript?
>> 
>> > :
>> >         nlminb problem, convergence error code =
>> 1;
>> > message = iteration limit reached without
>> convergence
>> > (9)
>> 
>> > Has anybody an idea to solve this problem?
>> 
>> Oh, I have lots of ideas but without a reproducible
>> example I can't
>> hope to decide what might be the problem.
>> 
>> It appears that the model may be over-parameterized.
>>  Assuming that
>> there are 4 different values of week then ~ week |
>> rep requires
>> fitting 10 variance-covariance parameters. That's a
>> lot.
>> The error code indicates that the optimizer is
>> taking
>>

>
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Received on Sat 15 Dec 2007 - 03:29:57 GMT

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