brms (version 1.9.0)

mo: Monotonic Predictors in brms Models

Description

Monotonic Predictors in brms Models

Usage

mo(expr)

Arguments

expr

Expression containing predictors, for which monotonic effects should be estimated. For evaluation, R formula syntax is applied.

Details

For detailed documentation see help(brmsformula) as well as vignette("brms_monotonic").

This function is almost solely useful when called in formulas passed to the brms package.

See Also

brmsformula

Examples

# NOT RUN {
  
# }
# NOT RUN {
# generate some data
income_options <- c("below_20", "20_to_40", "40_to_100", "greater_100")
income <- factor(sample(income_options, 100, TRUE), 
                 levels = income_options, ordered = TRUE)
mean_ls <- c(30, 60, 70, 75)
ls <- mean_ls[income] + rnorm(100, sd = 7)
dat <- data.frame(income, ls)

# fit a simple monotonic model
fit <- brm(ls ~ mo(income), data = dat)

# summarise the model
summary(fit)
plot(fit, N = 6)
plot(marginal_effects(fit), points = TRUE)
# }
# NOT RUN {
 
# }