
FYI, I think Lucia is referring to advice such as this:
http://davidhughjones.blogspot.com/2009/11/lme-false-convergence.html 
I can't speak to whether this actually does or does not help, but I guess the idea is that convergence may be helped if there are not any very small or very large values of the parameters being estimated.
Jake
> Date: Thu, 21 Jun 2012 01:17:43 +0100
> From: highstat@highstat.com
> To: r-sig-mixed-models@r-project.org
> Subject: Re: [R-sig-ME] How to include autocorrelation in GLMM and what to do with, false convergence warning message appearing after including an, interaction term (Lucia)
> 
> 
> 
>   > I will try to explain my data as good as possible.
> >> So we taged 13 different whales with a tag that records time, depth,
> >> speed, angle of descent and ascent 25 samples every second.
> >> The normal diving behaviour of these animals is one deep dive of one
> >> hour to 1200 meters followed by a series of 3-7 shallow dives of 20
> >> minutes up to 300 m. Because the tag not always stays the same time
> >> in each animal, my data is unbalanced and some tag records have one
> >> deep dive and 6 shallow dives while other records have 7 deep dives
> >> and 26 shallow dives.
> >> I divided each dive in units of 30 seconds. for each unit I have the
> >> next data:
> >> whale number, dive number, total number of fluke strokes in the 30
> >> seconds unit of analysis, mean of the sin of the angle during the 30
> >> seconds unit, swim speed, dive type(ascent or descent), dive
> >> direction( if it is a descent or an ascent) and time since the start
> >> of the dive and finally my variable response which is presence or
> >> absence of one type of fluke stroke called stroke type B.
> >>
> >> I think there has to be some autocorrelation between each 30 seconds
> >> unit of analyis and need to include it in my model but do not know how!
> >>
> >> I am interested to know what affects the presence or absence of the
> >> type B stroke (which is a binomial variable with 0 and 1)
> >> so I decide to use a  binomial glmm with whale number as a random
> >> effect. I included as well dive number within whale as a random effect.
> >>
> >> here is the model.
> >>
> >>
> >> glmm114<-lmer (StrokeB~ Time *
> >> Depth+SINP+flukes*Depth+speed+(1|whale_number)+(0+dive_number|whale_number),data=Luciadeepas,
> >> family = binomial)
> 
> 
> 
> 13 tagged animals may represent a lot of work....but it is not that much for a random intercept (and slope!).
> Perhaps dropping the random slope may avoid the warning message. Also...depth and speed sound like "collinearity"??
> 
> 
> 
> 
> 
> >>
> >> this is my final model after taking out the non significative
> >> variables, the problem is that due to the interaction a problem
> >> appears saying
> 
> 
> Check whether the quality/quantity of your data supports an interaction. There is always a reason if there is trouble.
> 
> 
> 
> 
> 
> 
> >>
> >> The false convergence warning message (8)
> >>
> >> I looked on internet and it says is a common problem,
> 
> 
> It is a common problem that people use too complicated models..:-)
> Or have data that are too limited for the type of models they want to use.
> 
> 
> 
> 
>   and some people
> >> says that it doesnt make any change in the output while others says
> >> that each variable has to be
> >> divided by 100.
> 
> 
> Better not believe everything people say. Divide by 100...huh????
> 
> 
> 
> 
> but when I do this then the variables that become
> >> significant doesnt make any sense.
> 
> 
> I don;t know what you divided by 100.....but in principle dividing the continuous covariates
> by 100 shouldn't change things that much. Unless you have some serious model misspecifications.
> 
> Perhaps you want to upload some data.
> 
> 
> 
> Alain
> 
>   >>
> >>
> >> Thanks so much in advanced
> >> Lucia
> 
> 
> 
> 
> 
> 
> -- 
> 
> Dr. Alain F. Zuur
> First author of:
> 
> 1. Analysing Ecological Data (2007).
> Zuur, AF, Ieno, EN and Smith, GM. Springer. 680 p.
> URL: www.springer.com/0-387-45967-7
> 
> 
> 2. Mixed effects models and extensions in ecology with R. (2009).
> Zuur, AF, Ieno, EN, Walker, N, Saveliev, AA, and Smith, GM. Springer.
> http://www.springer.com/life+sci/ecology/book/978-0-387-87457-9
> 
> 
> 3. A Beginner's Guide to R (2009).
> Zuur, AF, Ieno, EN, Meesters, EHWG. Springer
> http://www.springer.com/statistics/computational/book/978-0-387-93836-3
> 
> 
> 4. Zero Inflated Models and Generalized Linear Mixed Models with R. (2012) Zuur, Saveliev, Ieno.
> http://www.highstat.com/book4.htm
> 
> Other books: http://www.highstat.com/books.htm
> 
> 
> Statistical consultancy, courses, data analysis and software
> Highland Statistics Ltd.
> 6 Laverock road
> UK - AB41 6FN Newburgh
> Tel: 0044 1358 788177
> Email: highstat@highstat.com
> URL: www.highstat.com
> URL: www.brodgar.com
> 
> _______________________________________________
> R-sig-mixed-models@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
 		 	   		  
	[[alternative HTML version deleted]]

