[R-sig-ME] MCMCglmm Prior for a Binary Trait with a Random Interaction w/ "animal"
c@meron@@o @end|ng |rom m@||@utoronto@c@
Thu Feb 27 23:04:35 CET 2020
I am trying to measure the genetic variance in plasticity when different plant genotypes are planted into two different environments. The trait of interest is binary (germination).
Without fitting an interaction term, the prior for a binary trait follows a Chi square distribution of df = 1, based on suggestions in de Villemereuil's (2012) paper. However, I wish to add an interaction term with my "animal" term (which is, actually in my case, the ID of a plant individual). If I wish to keep this prior for an interaction between the environment (a.k.a treatment), should I specify the covariance matrix in the alpha.V or V section of the prior?
Essentially, I want to incorporate suggestions made in Arnold et al. (2019)'s paper.
Below is my code:
prior_germ <- list(R = list(V = 1, fix = 1),
G = list(G1 = list(V = 1, nu = 1000, alpha.mu = 0, alpha.V = diag(2)),
G2 = list(V = 1, nu = 1000, alpha.mu = 0, alpha.V = diag(2))))
MCMCglmm(germ ~ treatment + plot, random = ~idh(treatment):animal + ~idh(treatment):animal,
ginverse = list(animal = Ainv),
family = "threshold", data = plastic.Germination, prior = prior_germ, #Bernoulli distribution
nitt = 1100000, thin = 500, burnin = 100000, verbose = T, pr = TRUE, trunc = TRUE)
Thanks for any advice in advance!
Master's Student | Plant Evolutionary Responses to Climate Change | Weis Lab
Department of Ecology & Evolutionary Biology
University of Toronto
ESC2083, St. George Campus
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