Fit Bayesian generalised (non-)linear multilevel compositional model via full Bayesian inference
Source:R/brmcoda.R
brmcoda.Rd
Fit a brm
model with multilevel ILR coordinates
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 inbrmsformula
.- ...
Further arguments passed to
brm
.
Value
A brmcoda
with two elements
complr
An object of class
complr
used in thebrm
model.model
An object of class
brmsfit
, which contains the posterior draws along with many other useful information about the model.
Examples
# \donttest{
if(requireNamespace("cmdstanr")){
x1 <- complr(data = mcompd, sbp = sbp,
parts = c("TST", "WAKE", "MVPA", "LPA", "SB"), idvar = "ID")
# inspect variables before passing to brmcoda
get_variables(x1)
## model with compositional predictor at between and within-person levels
m1 <- brmcoda(complr = x1,
formula = Stress ~ bz1_1 + bz2_1 + bz3_1 + bz4_1 +
wz1_1 + wz2_1 + wz3_1 + wz4_1 + (1 | ID),
chain = 1, iter = 500,
backend = "cmdstanr")
## model with compositional outcome
m2 <- brmcoda(complr = x1,
formula = mvbind(z1_1, z2_1, z3_1, z4_1) ~ Stress + Female + (1 | ID),
chain = 1, iter = 500,
backend = "cmdstanr")
## model with compositional predictor and outcome
x2 <- complr(data = mcompd,
parts = list(c("TST", "WAKE"), c("MVPA", "LPA", "SB")),
total = list(c(480), c(960)),
idvar = "ID",
transform = "ilr")
m3 <- brmcoda(complr = x2,
formula = mvbind(z1_2, z2_2) ~ z1_1 + Female + (1 | ID),
chain = 1, iter = 500,
backend = "cmdstanr")
}# }
#> Error in get_variables(x1): could not find function "get_variables"