Wald confidence intervals for brsmm models

Wald confidence intervals for brsmm models

Usage

# S3 method for class 'brsmm'
confint(
  object,
  parm,
  level = 0.95,
  model = c("full", "mean", "precision", "random"),
  ...
)

Arguments

object

A fitted "brsmm" object.

parm

Character or integer: which parameters.

level

Confidence level (default 0.95).

model

Character: "full", "mean", "precision", or "random".

...

Currently ignored.

Value

Matrix with columns for lower and upper confidence bounds.

See also

brsmm, coef.brsmm, vcov.brsmm

Examples

# \donttest{
dat <- data.frame(
  y = c(
    0, 5, 20, 50, 75, 90, 100, 30, 60, 45,
    10, 40, 55, 70, 85, 25, 35, 65, 80, 15
  ),
  x1 = rep(c(1, 2), 10),
  id = factor(rep(1:4, each = 5))
)
prep <- brs_prep(dat, ncuts = 100)
#> brs_prep: n = 20 | exact = 0, left = 1, right = 1, interval = 18
fit <- brsmm(y ~ x1, random = ~ 1 | id, data = prep)
confint(fit, model = "mean")
#>                 2.5 %    97.5 %
#> (Intercept) -1.174693 2.0168622
#> x1          -1.313782 0.6391828
# }