Short summary of the problem
I would like to know how to calculate the phylogenetic signal for models with varying slopes and intercepts. Following from https://cran.r-project.org/web/packages/brms/vignettes/brms_phylogenetics.html
If I have a Phylogenetic Model with repeated Measurements, but also with varying slopes (below), how does it affect the formula for
hypothesis() given in the original example?
model_repeat1 <- brm( phen ~ cofactor1*cofactor2 + (1|gr(phylo, cov = A)) + (1+cofactor1+cofactor2|species), data = data_repeat, family = gaussian(), data2 = list(A = A), prior = c( prior(normal(0,10), "b"), prior(normal(0,50), "Intercept"), prior(student_t(3,0,20), "sd"), prior(student_t(3,0,20), "sigma") ), sample_prior = TRUE, chains = 2, cores = 2, iter = 4000, warmup = 1000 )
- Operating System: Windows 11 (64-bit operating system)
- brms Version: 2.20.1