[R-sig-ME] ZIGLMM for count and temporal data

[Highland Statistics Ltd]

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Subject: 	R-sig-mixed-models Digest, Vol 131, Issue 19
Date: 	Mon, 20 Nov 2017 17:28:14 +0100
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Today's Topics:

    1. ZIGLMM for count and temporal data (Anton Baotic)
    2. Re: lme4 merMod model object (Fox, John)
    3. Problems fitting GLMM and getting AIC (Mario Garrido)
    4. Two-part question about inference and model structure (Dan)


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Message: 1
Date: Mon, 20 Nov 2017 14:44:07 +0100
From: Anton Baotic <anton.baotic at univie.ac.at>
To: r-sig-mixed-models at r-project.org
Subject: [R-sig-ME] ZIGLMM for count and temporal data
Message-ID: <a499b9a2d3960f4abe66944a11522c97 at univie.ac.at>
Content-Type: text/plain; charset=US-ASCII; format=flowed

Hello,

I am new to R and came across the glmmamdb package. I hope you can
answer my question.

Very briefly, I conducted acoustic playback experiments where I
presented an animal species' with calls (of the same species) that
simulate different body size (smaller, same-sized, or larger) to
investigate whether a preference to a particular body size exists. For
the analysis I am using temporal variables such as 'approach' (in
seconds) or for example frequency/counts of ear lifts'... with size
category (of each presented call AND test animal) as fixed and identity
(of the exemplar animal AND test individual) as random effect...
However, some test subjects showed no reaction at all (meaning
zero-inflation for count and durational variables).
My question would be whether variables measured in seconds are at all
suitable for the ZIGLMM? If yes, does the ZIGLMM allows to use count and
temporal variables together in a single analysis?

Thank you so much!

Best
Anton



Anton,

Not sure whether I understand your question. But why don't you write out the equation
of the model that you intend to apply? That forces you to think, and makes communication easier.
Also..excessive number of zeros does not mean that you have to apply zero-inflated models.
And besides glmmADMB, I would also have a look at glmmTMB.

If your measurements are over time (be it seconds, days or years), then you may need to take temporal correlation into account. Have a look
at R-INLA in that case.

Measurements made in seconds sounds like a lot of data.

Kind regards,

Alain




-- 

Dr. Alain F. Zuur
Highland Statistics Ltd.
9 St Clair Wynd
AB41 6DZ Newburgh, UK
Email: highstat at highstat.com
URL:   www.highstat.com

And:
NIOZ Royal Netherlands Institute for Sea Research,
Department of Coastal Systems, and Utrecht University,
P.O. Box 59, 1790 AB Den Burg,
Texel, The Netherlands



Author of:
1. Beginner's Guide to Spatial, Temporal and Spatial-Temporal Ecological Data Analysis with R-INLA. (2017).
2. Beginner's Guide to Zero-Inflated Models with R (2016).
3. Beginner's Guide to Data Exploration and Visualisation with R (2015).
4. Beginner's Guide to GAMM with R (2014).
5. Beginner's Guide to GLM and GLMM with R (2013).
6. Beginner's Guide to GAM with R (2012).
7. Zero Inflated Models and GLMM with R (2012).
8. A Beginner's Guide to R (2009).
9. Mixed effects models and extensions in ecology with R (2009).
10. Analysing Ecological Data (2007).


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