[R-sig-ME] Bradley Terry GLMM in R ?

Thierry Onkelinx th|erry@onke||nx @end|ng |rom |nbo@be
Fri Oct 7 16:18:48 CEST 2022


Hi Shira,

I fit such models with the INLA package (https://www.r-inla.org/). The
trick is to define two random effects but force their parameter estimates
to be identical.

The code would contain something like f(home, model = "iid")) + f(away,
copy = "home"). Meaning home ~ N(0, sigma_beta_i) and home[i] = away[i]

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 using inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be

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Op vr 7 okt. 2022 om 15:00 schreef Shira Mitchell <shiraqotj using gmail.com>:

> We want to fit Bradley-Terry-style GLMM models in R. We looked into:
>
>
> https://cran.r-project.org/web/packages/BradleyTerry2/vignettes/BradleyTerry.pdf
> and
> http://bbolker.github.io/mixedmodels-misc/glmmFAQ.html
>
> We have voter-specific variables x that influence which political message
> (i vs j) wins for them:
>
> logit[pr(i beats j | person with covariate x)] = lambda_i - lambda_j +
> (beta_i - beta_j) x
>
> We then model parameters as random effects:
> lambda_i ~ N(0, sigma_lambda)
> beta_i ~ N(0, sigma_beta)
>
> Is there a way to do this in R ? We do this in TensorFlow in Python by
> directly specifying design matrices with the 0,-1,1 or 0,-x,x entries.
> However, I do not see how to do this in R using lme4, BradleyTerry2, mgcv,
> etc.
>
> Thanks so much,
> Shira
>
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>
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