lmerTest: legacy – R documentation

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legacy

Methods for Legacy lmerTest Objects

Description

Methods are defined for legacy lmerTest objects of class merModLmerTest generated with lmerTest version < 3.0-0. These methods are defined by interfacing code for lmerModLmerTest methods and therefore behaves like these methods do (which may differ from the behavior of lmerTest version < 3.0-0.)

Usage

## S3 method for class 'merModLmerTest'
anova(
  object,
  ...,
  type = c("III", "II", "I", "3", "2", "1"),
  ddf = c("Satterthwaite", "Kenward-Roger", "lme4")
)

## S3 method for class 'merModLmerTest'
summary(object, ..., ddf = c("Satterthwaite", "Kenward-Roger", "lme4"))

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

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

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

## S3 method for class 'merModLmerTest'
drop1(
  object,
  scope,
  ddf = c("Satterthwaite", "Kenward-Roger", "lme4"),
  force_get_contrasts = FALSE,
  ...
)

## S3 method for class 'merModLmerTest'
step(
  object,
  ddf = c("Satterthwaite", "Kenward-Roger"),
  alpha.random = 0.1,
  alpha.fixed = 0.05,
  reduce.fixed = TRUE,
  reduce.random = TRUE,
  keep,
  ...
)

Arguments

`object`	an `lmerModLmerTest` object; the result of `lmer()` after loading the lmerTest-package.
`...`	for the anova method optionally additional models; for other methods see the corresponding `lmerModLmerTest` methods for details.
`type`	the type of ANOVA table requested (using SAS terminology) with Type I being the familiar sequential ANOVA table.
`ddf`	the method for computing the denominator degrees of freedom and F-statistics. `ddf="Satterthwaite"` (default) uses Satterthwaite's method; `ddf="Kenward-Roger"` uses Kenward-Roger's method, `ddf = "lme4"` returns the lme4-anova table, i.e., using the anova method for `lmerMod` objects as defined in the lme4-package and ignores the `type` argument. Partial matching is allowed.
`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.
`pairwise`	compute pairwise differences of LS-means instead?
`scope`	optional character vector naming terms to be dropped from the model. Note that only marginal terms can be dropped. To see which terms are marginal, use `drop.scope(terms(object))`.
`force_get_contrasts`	enforce computation of contrast matrices by a method in which the design matrices for full and restricted models are compared.
`alpha.random`	alpha for random effects elimination
`alpha.fixed`	alpha for fixed effects elimination
`reduce.fixed`	reduce fixed effect structure? `TRUE` by default.
`reduce.random`	reduce random effect structure? `TRUE` by default.
`keep`	an optional character vector of fixed effect terms which should not be considered for eliminated. Valid terms are given by `attr(terms(object), "term.labels")`. Terms that are marginal to terms in keep will also not be considered for eliminations.

Author(s)

Rune Haubo B. Christensen

Examples

# Load model fits fm1 and fm2 generated with lmerTest version 2.3-37:
load(system.file("testdata","legacy_fits.RData", package="lmerTest"))

# Apply some methods defined by lmerTest:
anova(fm1)
summary(fm1)
contest(fm1, c(0, 1))
contest(fm1, c(0, 1), joint=FALSE)
drop1(fm1)
ranova(fm1)

# lme4-methods also work:
fixef(fm1)

# Ditto for second model fit:
anova(fm2)
summary(fm2)
ls_means(fm2)
difflsmeans(fm2)

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