Bradley Terry GLMM in R ?
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 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 vr 7 okt. 2022 om 15:00 schreef Shira Mitchell <shiraqotj at 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 [[alternative HTML version deleted]]
_______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models