[prev in list] [next in list] [prev in thread] [next in thread]
List: r-sig-mixed-models
Subject: Re: [R-sig-ME] a GlmmTMB advice
From: Ben Bolker <bbolker () gmail ! com>
Date: 2020-05-26 0:48:54
Message-ID: 439f0884-0259-4ddb-7ef9-11447b96c3a2 () gmail ! com
[Download RAW message or body]
No need to apologize (but do, please, keep the mailing list in the Cc:)
Are you running/planning to run 16 separate abundance analyses? If
so, see comments below ...
On 5/25/20 8:40 PM, Leida Dos Santos wrote:
> There are 486 individuals of 16 different species ! Sorry !
>
> Get Outlook for iOS <https://aka.ms/o0ukef>
> ------------------------------------------------------------------------
> *From:* Ben Bolker <bbolker@gmail.com>
> *Sent:* Tuesday, May 26, 2020 1:38:09 AM
> *To:* Leida Dos Santos <ldossantos@amphibians.org>;
> r-sig-mixed-models@r-project.org <r-sig-mixed-models@r-project.org>
> *Subject:* Re: [R-sig-ME] a GlmmTMB advice
>
> [please keep the mailing list in Cc:]
>
> On 5/25/20 8:31 PM, Leida Dos Santos wrote:
>> Thank very much Ben,
>> >There are 19 different specimens<- I mean 19 different species
>> (specimens in portuguese, I am sorry!)
>
>
> OK.
>
>>
>> Ben I am concerned because after checking the data carefully, I have
>> noticed that some 13 of the 16 different species there are less than
>> 10 individuals per species. Would it be ok to run the Glmm anyways? I
>> am modelling the abundance as response variable and
>> predictor variables year/month (the month of sampling for each year),
>> species, climate data (tmax, tmin, precipitation, and species life
>> traits history (size, habitat, habit, etc).
>
> I don't see immediately why this would be a problem with the
> species-richness analysis.
>
> Are you running 19 (or 16, I can't tell how many species there
> really are) separate abundance analyses? That's going to be very
> difficult if you have small numbers of individuals per species. Also,
> if you run 19 analyses with 8 covariates each, the chances of getting
> a lot of false positives/need for some kind of shrinkage or
> multiple-comparisons correction goes up. (This is not really a mixed
> modeling question, more a generic question of what to do with
> relatively small, noisy ecological data sets ...)
>
>
>>
>> I am sorry for not being able to formulate my questions properly.
>>
>> Kind regards,
>>
>>
>>
>>
>>
>> *Leida Dos Santos*
>> */BSc/**/,QTS,MSc,/**/PhD/*
>> /_**_*IUCN SSC ASG*** Programme *Officer*/
>> /ldossantos@amphibians.org <mailto:ldossantos@amphibians.org>/
>> _leidamphibian@gmail.com <mailto:leidamphibian@gmail.com>_
>> */@anfileida/*
>> */http://www.amphibians.org//*
>> **/http://www.nzfrogs.org/**
>> *0 0*
>> * ( -- )
>> /\( )/\
>> ^^ ^^ ^^ ^^
>> **PS: Please consider the environment before printing this E-mail*
>>
>>
>>
>>
>>
>> On Mon, 25 May 2020 at 17:44, Ben Bolker <bbolker@gmail.com
>> <mailto:bbolker@gmail.com>> wrote:
>>
>>
>> On 5/20/20 11:19 AM, Leida Dos Santos wrote:
>> > Hello there, I was wondering if you help. I am still learning
>> how to work
>> > with GlmmTMB and I have fitted GlmmTMB before but for
>> categorical data . I
>> > currently am working on a paper and have a data set where I am
>> trying to
>> > fit a GlmmTMB. I want to show the effect climate data on
>> species richness
>> > and abundance . I have fitted the predictor response with
>> species "Richness
>> > Index" and another with "abundance ", and predictor variables
>> "climate
>> > data" such as tmax, tmin, precipitation (Richness index I
>> calculated using
>> > vegan package). I have fitted (site and Month) as random
>> intercept, because
>> > the data was collected with no consistency but random days and
>> month, and
>> > years (2010-2019).
>>
>> does the Month variable include both month and year (e.g.
>> 2010.April, 2018.May)?
>>
>> > There are 19 different specimens
>>
>> Not sure what this means ...
>>
>> > and n= 467. All
>> > variables are numerical. #Global Model example: Abun_2<-
>> glmmTMB(Richness ~
>> > (tmin +ppt1 + tmax1 + tmax2 +tmin2+ ppt2 + Year)^2+ (1|Site/Month),
>> > data=Main_data, family="nbinom2"). However when I run this
>> model, I come
>> > across some warning messages:
>> >
>> > "Found more than one class "Matrix" in cache; using the first, from
>> > namespace 'Matrix'
>> > Also defined by ‘arkhe’
>>
>> This is harmless is in this case (although it seems like a
>> questionable decision on the part of the arkhe package developers).
>>
>> > Warning messages:
>> > _1: In glmmTMB(Abundance ~ (tmin + ppt + tmax2 + tmax + tmin2 +
>> ppt2 + :
>> > non-integer counts in a nbinom2 model
>> > 2: In fitTMB(TMBStruc) :
>> > Model convergence problem; non-positive-definite Hessian
>> matrix. See
>> > vignette('troubleshooting')
>> > 3: In fitTMB(TMBStruc) :
>> > Model convergence problem; function evaluation limit reached
>> without
>> > convergence (9). See vignette('troubleshooting')".
>> >
>> > I checked vignette, but the truth is, this is too advanced for
>> and I do not
>> > understand what it is saying:) I would love to have some
>> feedback with
>> > regards to the model. Additionally, should I use just count for
>> Richness
>> > instead of the Menhinick index for richness? Or should I use a
>> completely
>> > different model? I
>>
>> The main issue here is that it almost never makes sense to use a
>> count-based model (nbinom1, nbinom2, Poisson) for data that are not
>> actual counts (i.e. integers). I'm not going to weigh in on which
>> index/model you should use; there are long discussions about
>> that, and
>> you should decide as much on biological grounds (what question
>> are you
>> trying to answer?) as statistical grounds. As long as the model
>> converges to a stable answer, and the assumptions of linearity and
>> homoscedasticity are reasonably well met, you should be OK
>> statistically.
>>
>> > would be very grateful for any feedback please:):) Thank
>> > you in advance. :x
>>
>>
>>
>> > *Leida Dos Santos*
>> > *BSc**,QTS,MSc,**PhD*
>> > *IUCN SSC ASG Programme Officer*
>> > *ldossantos@amphibians.org <mailto:ldossantos@amphibians.org>
>> <ldossantos@amphibians.org <mailto:ldossantos@amphibians.org>>*
>> > *leidamphibian@gmail.com <mailto:leidamphibian@gmail.com>
>> <leidamphibian@gmail.com <mailto:leidamphibian@gmail.com>>*
>> > *@anfileida*
>> > *http://www.amphibians.org/ <http://www.amphibians.org/>*
>> > *http://www.nzfrogs.org <http://www.nzfrogs.org>*
>> > *0 0*
>> >
>> >
>> >
>> > * ( -- ) /\( )/\^^ ^^ ^^ ^^**PS: Please consider the
>> > environment before printing this E-mail*
>> >
>> > [[alternative HTML version deleted]]
>> >
>> > _______________________________________________
>> > R-sig-mixed-models@r-project.org
>> <mailto:R-sig-mixed-models@r-project.org> mailing list
>> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>> <https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models>
>>
>> _______________________________________________
>> R-sig-mixed-models@r-project.org
>> <mailto:R-sig-mixed-models@r-project.org> mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>
[[alternative HTML version deleted]]
_______________________________________________
R-sig-mixed-models@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
[prev in list] [next in list] [prev in thread] [next in thread]
Configure |
About |
News |
Add a list |
Sponsored by KoreLogic