pbkrtest (version 0.5.5)

get_ddf_Lb: Adjusted denominator degrees of freedom for linear estimate for linear mixed model.

Description

Get adjusted denominator degrees freedom for testing Lb=0 in a linear mixed model where L is a restriction matrix.

Usage

get_Lb_ddf(object, L)
# S3 method for lmerMod
get_Lb_ddf(object, L)
Lb_ddf(L, V0, Vadj)
get_ddf_Lb(object, Lcoef)
# S3 method for lmerMod
get_ddf_Lb(object, Lcoef)
ddf_Lb(VVa, Lcoef, VV0 = VVa)

Value

Adjusted degrees of freedom (adjustment made by a Kenward-Roger approximation).

Arguments

object

A linear mixed model object.

L

A vector with the same length as fixef(object) or a matrix with the same number of columns as the length of fixef(object)

V0, Vadj

The unadjusted and the adjusted covariance matrices for the fixed effects parameters. The unadjusted covariance matrix is obtained with vcov() and adjusted with vcovAdj().

Lcoef

Linear contrast matrix

VVa

Adjusted covariance matrix

VV0

Unadjusted covariance matrix

Author

Søren Højsgaard,

References

Ulrich Halekoh, Søren Højsgaard (2014)., A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models - The R Package pbkrtest., Journal of Statistical Software, 58(10), 1-30., https://www.jstatsoft.org/v59/i09/

See Also

KRmodcomp, vcovAdj, model2restriction_matrix, restriction_matrix2model

Examples

(fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
(fm0 <- lmer(Reaction ~ 1 + (Days|Subject), sleepstudy))
anova(fm1, fm0)

KRmodcomp(fm1, fm0)  ## 17 denominator df's
get_Lb_ddf(fm1, c(0, 1)) ## 17 denominator df's

# Notice: The restriction matrix L corresponding to the test above
# can be found with
L <- model2restriction_matrix(fm1, fm0)
L