parameters (version 0.12.0)

bootstrap_model: Model bootstrapping

Description

Bootstrap a statistical model n times to return a data frame of estimates.

Usage

bootstrap_model(model, iterations = 1000, verbose = FALSE, ...)

Arguments

model

Statistical model.

iterations

The number of draws to simulate/bootstrap.

verbose

Toggle warnings and messages.

...

Arguments passed to or from other methods.

Value

A data frame of bootstrapped estimates.

Using with <code>emmeans</code>

The output can be passed directly to the various functions from the emmeans package, to obtain bootstrapped estimates, contrasts, simple slopes, etc, and their confidence intervals. These can then be passed to model_parameter() to obtain standard errors, p-values, etc (see example).

Note that that p-values returned here are estimated under the assumption of translation equivariance: that shape of the sampling distribution is unaffected by the null being true or not. If this assumption does not hold, p-values can be biased, and it is suggested to use proper permutation tests to obtain non-parametric p-values.

See Also

bootstrap_parameters, simulate_model, simulate_parameters

Examples

# NOT RUN {
if (require("boot")) {
  model <- lm(mpg ~ wt + factor(cyl), data = mtcars)
  b <- bootstrap_model(model)
  print(head(b))

  if (require("emmeans")) {
    est <- emmeans(b, consec ~ cyl)
    print(model_parameters(est))
  }
}
# }