[R-sig-ME] error: model is nearly unidentifiable
Ligia Pizzatto do Prado
ligia_oceanica at hotmail.com
Mon Apr 9 08:14:09 CEST 2018
Hi there, I'm new to mixed models but have ran a few with success before. Now, while trying to analyse this new experiment I am having an error that I quite don't understand...
The experiment is a two choice habitat ("choice": poor  vs rich ) for frogs under two-state treatments, lets say F and C. Then I have as potential variables frog size ("size"), air temperature ("temp"), humidity ("hum") and date of experiment (recorded as continuos variable starting at day 1...). This is a repeated measure design as frogs were tested both in F and C trials (thus id is my random effect). I want to know if the choice is affected by treat, but also considering size, temp, humidity, and date in my model.
First I did:
treat id choice
C:24 1 : 2 0:24
F:24 2 : 2 1:24
3 : 2
4 : 2
5 : 2
6 : 2
size temp hum date
Min. :35.70 Min. :24.80 Min. :53.00 Min. : 1.00
1st Qu.:38.25 1st Qu.:26.30 1st Qu.:58.50 1st Qu.: 4.00
Median :42.40 Median :27.30 Median :63.00 Median : 9.00
Mean :42.02 Mean :26.74 Mean :63.65 Mean :10.75
3rd Qu.:44.27 3rd Qu.:27.40 3rd Qu.:70.50 3rd Qu.:16.75
Max. :51.00 Max. :27.90 Max. :76.00 Max. :24.00
m1<- glmer(Fchoice ~ treat + SUL + temp + hum + date + (1|id), data = data, family = binomial)
In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model is nearly unidentifiable: large eigenvalue ratio
- Rescale variables?
I keep getting this message in all models except when I exclude both temp and hum, but I also get the message when tried null model: null<- glmer(choice ~ 1 + (1|id), data = data, family = binomial)
I tried to transform/re-scale all continuous variable (temp, hum, date) and nothing changed, and I quite don't understand why the error also appears in the null model, given id is a factor... If its a scale problem wouldn't this only appear in the continuous variables?
Can anyone provide some guidance here, please?
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