Summarise a vcmm fit — summary.vcmm

Produces a vcmm_summary object with a coefficient table for the fixed-effects, the variance components, and basic fit diagnostics. print() renders it in the style of lm / lmer.

Usage

# S3 method for class 'vcmm_fit'
summary(object, ...)

# S3 method for class 'vcmm_summary'
print(
  x,
  digits = max(3L, getOption("digits") - 3L),
  signif.stars = getOption("show.signif.stars"),
  ...
)

Arguments

object: A vcmm_fit object.
...: Unused.
x: A vcmm_summary object.
digits: Integer. Number of significant digits to display.
signif.stars: Logical. If TRUE, append significance stars to the coefficient table.

Value

A list of class "vcmm_summary".

Details

The standard errors are the square roots of the diagonal of vcov(object, which = "beta"), treating \(\sigma_\varepsilon\) and \(\sigma_\alpha\) (or \(\Sigma_\alpha\)) as fixed at their fitted values. They are first-order valid (Theorem 3.1) but do not adjust for variance-component uncertainty.

For re_cov %in% c("kronecker", "separable"), the variance- components block of the printed summary displays the estimated \(\Sigma_{\mathrm{left}}\) (\(\Sigma_{2\times 2}\) for OD or \(\Sigma_q\) for group-shared dense) instead of a scalar \(\sigma_\alpha\).