Fit Bayesian generalised (non-)linear multilevel compositional model via full Bayesian inference
Fit Bayesian generalised (non-)linear multilevel compositional model via full Bayesian inference
Fit a brm model with multilevel ILR coordinates
brmcoda(complr, formula,...)
Arguments
complr: A complr object containing data of composition, ILR coordinates, and other variables used in the model.
formula: A object of class formula, brmsformula: A symbolic description of the model to be fitted. Details of the model specification can be found in brmsformula.
...: Further arguments passed to brm.
Returns
A brmcoda with two elements - complr: An object of class complr used in the brm model.
model: An object of class brmsfit, which contains the posterior draws along with many other useful information about the model.
Examples
if(requireNamespace("cmdstanr")){ cilr <- complr(data = mcompd, sbp = sbp, parts = c("TST","WAKE","MVPA","LPA","SB"), idvar ="ID")# inspects ILRs before passing to brmcoda names(cilr$between_logratio) names(cilr$within_logratio) names(cilr$logratio)# model with compositional predictor at between and within-person levels m1 <- brmcoda(complr = cilr, formula = Stress ~ bilr1 + bilr2 + bilr3 + bilr4 + wilr1 + wilr2 + wilr3 + wilr4 +(1| ID), chain =1, iter =500, backend ="cmdstanr")# model with compositional outcome m2 <- brmcoda(complr = cilr, formula = mvbind(ilr1, ilr2, ilr3, ilr4)~ Stress + Female +(1| ID), chain =1, iter =500, backend ="cmdstanr")}