[R-sig-ME] zero one inflated beta mixed model

[Morgane Brachet]

Thank you very much for your help, I will look into it!

Morgane
________________________________
De : jonnations <jonnations using gmail.com>
Envoy� : mercredi 12 f�vrier 2020 21:37
� : morgane.brachet using hotmail.com <morgane.brachet using hotmail.com>
Cc : r-sig-mixed-models using r-project.org <r-sig-mixed-models using r-project.org>
Objet : Re: [R-sig-ME] zero one inflated beta mixed model

Hi Morgane,

Like Ben said, brms is a good option for zero one inflated beta models.
I have used proportional data in the past and, when learning about mixed models, was surprised to find out that there is no obvious distribution family for these data. In my own experience zero one inflated models required more data than I had to make good parameter estimates. Depending on the distribution of your data, an ordinal model could be a good choice! You could set lots of thresholds if you want. There is a great manuscript&tutorial on ordinal models in brms available here https://psyarxiv.com/x8swp/  I think there is a formatted published version out there for free as well.


Message: 2
Date: Wed, 12 Feb 2020 09:56:44 -0500
From: Ben Bolker <bbolker using gmail.com<mailto:bbolker using gmail.com>>
To: Morgane Brachet <morgane.brachet using hotmail.com<mailto:morgane.brachet using hotmail.com>>
Cc: "r-sig-mixed-models using r-project.org<mailto:r-sig-mixed-models using r-project.org>"
        <r-sig-mixed-models using r-project.org<mailto:r-sig-mixed-models using r-project.org>>
Subject: Re: [R-sig-ME] zero one inflated beta mixed model
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    At present glmmTMB doesn't do zero-one-inflated betas, only
zero-inflated betas. As far as I know your options are (1) use brms,
(2) squish your 1 values to something slightly less than 1, or (3) do
the hurdle model manually (i.e. fit two separate models, one for the
probability that the response== 1, and another (conditional) model for
the zero-inflated beta distribution applied only to the responses <1).

  Others on the list may have other suggestions ... (e.g. does INLA
does zero-one-inflated betas?)

On Wed, Feb 12, 2020 at 8:42 AM Morgane Brachet
<morgane.brachet using hotmail.com<mailto:morgane.brachet using hotmail.com>> wrote:
>
> Hello,
>
> I am writing to you following one of the posts on GitHub (https://github.com/glmmTMB/glmmTMB/issues/355). I am trying to fit proportion data with lots of 0s and a few 1s into a hurdle model using glmmTMB. Is this possible? Would you have any example code please?
>
> Thank you!
>
> Morgane
> [https://avatars1.githubusercontent.com/u/13640228?s=400&v=4]<https://github.com/glmmTMB/glmmTMB/issues/355>
> zero inflation for beta distribution model � Issue #355 � glmmTMB/glmmTMB � GitHub<https://github.com/glmmTMB/glmmTMB/issues/355>
> Hi Ben, Thanks for your reply. To fit hurdle model using glmmTMB, do you have any example code? will it still have the same issue? Actually i thought using the ziformula option is the way to fit hurdle model, but since it shows such errors of inappropriate values, i guess i may misse some options for hurdle model.
> github.com<http://github.com>
>
>
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--
Jonathan A. Nations
PhD Candidate
Esselstyn Lab<https://esselstyn.github.io/>
Museum of Natural Sciences<https://www.lsu.edu/mns/>
Louisiana State University
jonnynations.com<https://jonnynations.com/>

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