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Failure to converge with glmer on gamma data

4 messages · moses selebatso, Ben Bolker

Original
moses selebatso
# 
Hello
I m trying to determine the effects of season and habitat on forage protein content. With my replica nested within location. 
model<-glmer(Protein~Habitat*Season + (1|Location/Replica), family=Gamma)
I am getting a warning when running my model. I have tried read on previous post and most?of the time?I get lost because I?fairly new to R.?I?understand there is a maximum "maxlgradl" of 0.001 that should be accepted in this kind of warnings. However, mine?is a?little higher?than that. Can someone advise how I can?proceed here and get an acceptable?output.
I also tried using "....family =Gamma(log)"? instead of just "....family = Gamma" and it doesn't give me the warning. Can this be an acceptable option? 
Model and output below. I can provide data sample if?needed.
Warning message:
In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,? :
? Model failed to converge with max|grad| = 0.00123611 (tol = 0.001, component 1)
Warning message:
In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,? :
? Model failed to converge with max|grad| = 0.00254076 (tol = 0.001, component 1)


?Thank you

Moses SELEBATSO Home:?? ?(+267) 318 5219 (H)??Mobile: ?(+267) 716 39370? or? (+267) 738 39370
Ben Bolker
# 
Short answers:

(1) the decision whether to use a log or an inverse link function is
at root a scientific one (i.e., is one functional form or the other
more sensible for your problem?), although it is generally the case
that log links are more stable.  You could also use AIC or
log-likelihood to choose among links if you wanted.
(2) I would say that 0.0025 is *probably* acceptable, although it
would be best to try a different optimizer and see if you get similar
results; have you read the ?convergence manual page?
On Sun, Mar 6, 2016 at 4:43 PM, moses selebatso <selebatsom at yahoo.co.uk> wrote:
moses selebatso
# 
Thank you for the response. I have just gone through the convergence manual in?lme4 February 2016. I ran the singularity test?and this is the result
[1] FALSE

My interpretation is that there is one (1) diagonal element?that is zero or very small. Is that correct? If?so, the manual says then "...the convergence??testing methods may be inappropriate.." I do not know what this means exactly. Does it mean I should not use the test or there is not need to do tests, and so accept the model? 
Thank you for your support and patience.
,
Moses SELEBATSO Home:?? ?(+267) 318 5219 (H)??Mobile: ?(+267) 716 39370? or? (+267) 738 39370
On Monday, 7 March 2016, 3:55, Ben Bolker <bbolker at gmail.com> wrote:
? Short answers:

(1) the decision whether to use a log or an inverse link function is
at root a scientific one (i.e., is one functional form or the other
more sensible for your problem?), although it is generally the case
that log links are more stable.? You could also use AIC or
log-likelihood to choose among links if you wanted.
(2) I would say that 0.0025 is *probably* acceptable, although it
would be best to try a different optimizer and see if you get similar
results; have you read the ?convergence manual page?
On Sun, Mar 6, 2016 at 4:43 PM, moses selebatso <selebatsom at yahoo.co.uk> wrote:

  
  


  


      

    

    

      
      

        


  

        

      Ben Bolker
    

    

      
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I think you've got this backwards:  FALSE means that the model
*isn't* singular (please re-read the docs, and if you think they're
unclear or wrong, post an issue at
http://github.com/lme4/lme4/issues).  So your model doesn't have that
particular problem.  (It's also fairly easy to identify singularity
for models with only scalar or 2-dimensional random effects -- just
look for zero variances or +/- 1 correlations.)

        
On Mon, Mar 7, 2016 at 1:53 AM, moses selebatso <selebatsom at yahoo.co.uk> wrote: