[R-sig-ME] Model average error message

[Helen McCallin]

Apologies, very new to this! I am currently away from my computer but as soon as I am home (within the hour) I will get those for you. 

Many thanks again 

Helen

> On 25 Jul 2018, at 16:09, Phillip Alday <phillip.alday using mpi.nl> wrote:
> 
> (Please keep the list in CC.)
> 
> The output of
> 
> get.models(models,subset=delta<5)
> 
> would be more interesting. Or even better:
> 
> lapply(get.models(models,subset=delta<5), formula)
> 
> So that we see which formulas are being labelled as identical.
> 
> Phillip
> 
>> On 07/25/2018 04:56 PM, Helen McCallin wrote:
>> Hi Phil
>> 
>> Thank you so much for your reply. Please find the codes I am using
>> below. Is this what you mean?
>> 
>> ae <- read.csv(file=file.choose())
>> 
>> options(na.action="na.fail")
>> 
>> global.model<-glmer(
>> 
>> 
>> cbind(numerator,total-numerator)~d+s+t+p+d:s:t:p+d:s:t+d:s:p+d:t:p+s:t:p+d:t+d:s+d:p+s:t+s:p+t:p+(1|random), 
>> 
>>     data=ae, family=binomial)   
>> 
>> options(max.print=1000000)
>> 
>> dredge(global.model,beta=c("none"),evaluate=TRUE,rank="AICc") 
>> 
>> ae.model <- glmer(
>> 
>> 
>> cbind(numerator,total-numerator)~d+s+t+p+d:s:t:p+d:s:t+d:s:p+d:t:p+s:t:p+d:t+d:s+d:p+s:t+s:p+t:p+(1|random),
>> 
>>    data=ae,family=binomial)
>> 
>> models <- dredge(ae.model)  
>> 
>> summary(model.avg(get.models(models,subset=delta<5)))
>> 
>> 
>> Many thanks for any help.
>> 
>> Best wishes
>> 
>> Helen
>> 
>> On 25 Jul 2018, at 13:50, Phillip Alday <phillip.alday using mpi.nl
>> <mailto:phillip.alday using mpi.nl>> wrote:
>> 
>>> Hi Helen,
>>> 
>>> model.avg() tells you which models are duplicates. What do the formulas
>>> look like for those models? Seeing the formulae may help identify what
>>> model.avg() gets stuck on.
>>> 
>>> Best,
>>> Phillip
>>> 
>>>> On 07/23/2018 11:33 AM, Helen McCallin wrote:
>>>> Hi
>>>> 
>>>> 
>>>> I am running a glmer model on a response variable with binomial
>>>> distribution and random term. My data has 3 explanatory categorical
>>>> variables and I have successfully run dredge() on them and their
>>>> interactions to get AICc values.
>>>> 
>>>> 
>>>> I want model averaging to provide output with coefficients and an
>>>> index of relative importance of fixed effects from those models;
>>>> within a delta constraint that I specify.I can get this using the
>>>> code below for alternative datasets but not for this dataset.
>>>> 
>>>> 
>>>> model.avg() produces this error message:
>>>> 
>>>> Error in model.avg.default(get.models(models, subset = delta < 5)) :
>>>> models are not unique. Duplicates: '2 = 3 = 4' and '10 = 11'
>>>> 
>>>> 
>>>> This doesn't make sense, DREDGE does not (cannot) produce duplicate
>>>> models – each model is a unique iteration within the full model, yet
>>>> the error message indicates that MODEL AVERAGE identified ‘duplicate’
>>>> models from within DREDGE output. R fails to run MODEL AVERAGE under
>>>> these circumstances - producing no further output.
>>>> 
>>>> 
>>>> Has anyone else experienced similar problem (with 'not unique',
>>>> duplicate models) via MODEL AVERAGE?
>>>> 
>>>> 
>>>> Is there a workaround for the error that prevents me running MODEL
>>>> AVERAGE due to perceived ‘duplicate’ models in DREDGE?
>>>> 
>>>> 
>>>> Many thanks for any help anyone can provide.
>>>> 
>>>> 
>>>> 
>>>>   [[alternative HTML version deleted]]
>>>> 
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