lmerTest: ls_means.lmerModLmerTest – R documentation

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ls_means.lmerModLmerTest

LS-means for lmerTest Model Fits

Description

Computes LS-means or pairwise differences of LS-mean for all factors in a linear mixed model. lsmeansLT is provided as an alias for ls_means for backward compatibility.

Usage

## S3 method for class 'lmerModLmerTest'
ls_means(
  model,
  which = NULL,
  level = 0.95,
  ddf = c("Satterthwaite", "Kenward-Roger"),
  pairwise = FALSE,
  ...
)

## S3 method for class 'lmerModLmerTest'
lsmeansLT(
  model,
  which = NULL,
  level = 0.95,
  ddf = c("Satterthwaite", "Kenward-Roger"),
  pairwise = FALSE,
  ...
)

## S3 method for class 'lmerModLmerTest'
difflsmeans(
  model,
  which = NULL,
  level = 0.95,
  ddf = c("Satterthwaite", "Kenward-Roger"),
  ...
)

Arguments

`model`	a model object fitted with `lmer` (of class `"lmerModLmerTest"`).
`which`	optional character vector naming factors for which LS-means should be computed. If `NULL` (default) LS-means for all factors are computed.
`level`	confidence level.
`ddf`	method for computation of denominator degrees of freedom.
`pairwise`	compute pairwise differences of LS-means instead?
`...`	currently not used.

Details

Confidence intervals and p-values are based on the t-distribution using degrees of freedom based on Satterthwaites or Kenward-Roger methods.

LS-means is SAS terminology for predicted/estimated marginal means, i.e. means for levels of factors which are averaged over the levels of other factors in the model. A flat (i.e. unweighted) average is taken which gives equal weight to all levels of each of the other factors. Numeric/continuous variables are set at their mean values. See emmeans package for more options and greater flexibility.

LS-means contrasts are checked for estimability and unestimable contrasts appear as NAs in the resulting table.

LS-means objects (of class "ls_means" have a print method).

Value

An LS-means table in the form of a data.frame. Formally an object of class c("ls_means", "data.frame") with a number of attributes set.

Author(s)

Rune Haubo B. Christensen and Alexandra Kuznetsova

Examples

# Get data and fit model:
data("cake", package="lme4")
model <- lmer(angle ~ recipe * temp + (1|recipe:replicate), cake)

# Compute LS-means:
ls_means(model)

# Get LS-means contrasts:
show_tests(ls_means(model))

# Compute pairwise differences of LS-means for each factor:
ls_means(model, pairwise=TRUE)
difflsmeans(model) # Equivalent.

lmerTest

Tests in Linear Mixed Effects Models

v3.1-3

GPL (>= 2)

Authors

Alexandra Kuznetsova [aut], Per Bruun Brockhoff [aut, ths], Rune Haubo Bojesen Christensen [aut, cre], Sofie Pødenphant Jensen [ctb]

Initial release