[R-sig-eco] Fitting a GLMM to a percent cover data with glmer or glmmTMB

[Botta-Dukát Zoltán]

I have to correct myself :),  because an important point is missing from 
this sentence:

Binomial distribution are defined as number of successes in independent 
trials.

correctly:

Binomial distribution are defined as number of successes in FIXED NUMBER 
OF independent trials.

Zoltan

2018. 11. 29. 15:23 keltezéssel, Botta-Dukát Zoltán írta:
> Hi,
>
> I'm sure that binomial is unsuitable for relative cover. Binomial 
> distribution are defined as number of successes in independent trials. 
> I think this scheme cannot be applied to relative cover or visually 
> estimated cover. It is important because both number of trials and 
> probability of success influence mean and variance, thus both should 
> have a meaning that correspond to terms in this scheme.
>
> Unfortunately, I have no experience with tweedie distribution. I am 
> also interested in experience of others! In theory an alternative 
> would be zero-inflated beta distribution (after rescaling percentage 
> between zero to one interval). Do some has an experience (including 
> its availability in R) with it?
>
> Cheers
>
> Zoltan
>
> 2018. 11. 28. 20:47 keltezéssel, Vasco Silva írta:
>> Hi,
>>
>> I am trying to fit a GLMM on percent cover for each species using glmer:
>>
>>> str(cover)
>> 'data.frame': 102 obs. of  114 variables:
>> $ Plot : Factor w/ 10 levels "P1","P10","P2",..: 1 1 1 1 1 3 3 ...
>> $ Sub.plot: Factor w/ 5 levels "S1","S2","S3",..: 1 2 3 4 5 1 2 ...
>> $ Grazing : Factor w/ 2 levels "Fenced","Unfenced": 1 1 1 1 1 1 1  ...
>> $ sp1 : int  0 0 0 1 0 0 1 ...
>> $ sp2 : int  0 0 0 0 0 3 3 ...
>> $ sp3 : int  0 1 0 0 1 3 3 ...
>> $ sp4 : int  1 3 13 3 3 3 0 ...
>> $ sp6 : int  0 0 0 0 0 0 0 ...
>>   ...
>> $ tot  : int  93 65 120 80 138 113 ...
>>
>> sp1.glmm <- glmer (cbind (sp1, tot- sp1) ~ Grazing + (1|Plot), 
>> data=cover,
>> family=binomial (link ="logit"))
>>
>> However, I wonder if binomial distribution can be used (proportion of
>> species cover from a total cover) or if I should  fitted the GLMM with
>> glmmTMB (tweedie distribution)?
>>
>> I would greatly appreciate it if someone could help me.
>>
>> Cheers.
>>
>> Vasco Silva
>>
>>     [[alternative HTML version deleted]]
>>
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