Quasi Poisson for glmm

    I agree with Thierry that the binomial is a good start.

    If you do find that there is overdispersion in your binomial model,
there are (at least) three possible approaches (see
http://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#overdispersion ):

   * beta-binomial model
   * observation-level random effects in a binomial model
   * quasi-binomial

   The last one is not available in glmmTMB, but the GLMM FAQ
http://bbolker.github.io/mixedmodels-misc/glmmFAQ.html shows you how to
get quasi-likelihood results if you want.

   cheers
     Ben Bolker


On 12/3/20 10:55 AM, Thierry Onkelinx via R-sig-mixed-models wrote:

Dear Faith,

I'd recommend starting with a full model with binomial distribution. What
you perceive as overdispersion in the response is often modelled by the
covariates.

Best regards,

ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE

AND

FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx at inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be

///////////////////////////////////////////////////////////////////////////////////////////

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to

say

what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of

data.

~ John Tukey

///////////////////////////////////////////////////////////////////////////////////////////

<https://www.inbo.be>


Op do 3 dec. 2020 om 16:17 schreef Ebhodaghe Faith <

ebhodaghefaith at gmail.com

:

Dear Thierry,
The proportions are on number of individuals infected by a parasite
divided by total number of individuals examined.

Thanks
Faith

On Thu, 3 Dec 2020, 4:48 p.m. Thierry Onkelinx, <

thierry.onkelinx at inbo.be>

wrote:

Dear Faith,

I missed to see you have a proportion response. The negative binomial

is

a (better) alternative for the quasi Poisson. But they assume count

data.

What kind of proportions do you have? Is it based on a number of
successes for a number of trials (binomial, beta binomial)? Or a

continuous

value between 0 and 1 (beta)?

Best regards,

ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx at inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be

///////////////////////////////////////////////////////////////////////////////////////////

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able

to say

what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does

not

ensure that a reasonable answer can be extracted from a given body of

data.

~ John Tukey

///////////////////////////////////////////////////////////////////////////////////////////

<https://www.inbo.be>


Op do 3 dec. 2020 om 13:14 schreef Ebhodaghe Faith <
ebhodaghefaith at gmail.com>:

Thanks, Thierry.

But could you please refer me to an article preferably in the

biological

sciences where a negative binomial distribution was used to model an
over-dispersed multilevel proportion response variable?

Thanks for your kind assistance.

Regards
Faith

On Thu, 3 Dec 2020, 1:32 p.m. Thierry Onkelinx, <
thierry.onkelinx at inbo.be> wrote:

Dear Faith,

You can use a negative binomial distribution.

Best regards,

ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR

NATURE

AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx at inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be

///////////////////////////////////////////////////////////////////////////////////////////

To call in the statistician after the experiment is done may be no

more

than asking him to perform a post-mortem examination: he may be able

to say

what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does
not ensure that a reasonable answer can be extracted from a given

body of

data. ~ John Tukey

///////////////////////////////////////////////////////////////////////////////////////////

<https://www.inbo.be>


Op do 3 dec. 2020 om 11:24 schreef Ebhodaghe Faith <
ebhodaghefaith at gmail.com>:

Hi All.

I have a dataset for wish I intend to model an over-dispersed
proportion
response variable with hierarchical structure. I tried using the

Quasi

Poisson family, but available packages including glmmTMB do not

allow

this.
What do you advice?

Thanks in advance for your kind response.

Faith Ebhodaghe
Nairobi, Kenya

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