Estimated marginal means for an lmm model

Marginal means use equal weights over nuisance-factor levels. Numeric covariates not listed in specs are held at their observed means. Multiplicity adjustment applies to pairwise p-values. Simultaneous Bonferroni confidence intervals are used automatically when p-values are adjusted, unless conf_adjust = "none" is requested.

Usage

lsmeans(
  object,
  specs,
  pairwise = FALSE,
  at = list(),
  level = 0.95,
  adjust = "none",
  conf_adjust = c("auto", "none", "bonferroni"),
  ...
)

Arguments

object

An lmm object.

specs

Variables defining the marginal means, supplied as a character vector or one-sided formula. Use pairwise ~ factor to request differences.

pairwise

Whether to return pairwise differences as well as means.

at

Named list overriding reference-grid values.

level

Confidence level.

adjust

Multiplicity adjustment passed to stats::p.adjust().

conf_adjust

Confidence-interval adjustment. "auto" uses Bonferroni intervals when adjust is not "none"; the alternatives are "none" and "bonferroni".

...

Reserved for future extensions.

Value

A tibble, or a list with lsmeans and contrasts tibbles when pairwise comparisons are requested.