get_ddf_Lb | R Documentation |
Get adjusted denominator degrees freedom for testing Lb=0 in a linear mixed model where L is a restriction matrix.
get_Lb_ddf(object, L) ## S3 method for class 'lmerMod' get_Lb_ddf(object, L) get_ddf_Lb(object, Lcoef) ## S3 method for class 'lmerMod' get_ddf_Lb(object, Lcoef) Lb_ddf(L, V0, Vadj) ddf_Lb(VVa, Lcoef, VV0 = VVa)
object |
A linear mixed model object. |
L |
A vector with the same length as |
Lcoef |
Linear contrast matrix |
V0, Vadj |
The unadjusted and the adjusted covariance matrices for the fixed
effects parameters. The unadjusted covariance matrix is obtained with
|
VVa |
Adjusted covariance matrix |
VV0 |
Unadjusted covariance matrix |
Adjusted degrees of freedom (adjustment made by a Kenward-Roger approximation).
Søren Højsgaard, sorenh@math.aau.dk
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/
KRmodcomp
, vcovAdj
,
model2restriction_matrix
,
restriction_matrix2model
(fmLarge <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)) ## removing Days (fmSmall <- lmer(Reaction ~ 1 + (Days|Subject), sleepstudy)) anova(fmLarge, fmSmall) KRmodcomp(fmLarge, fmSmall) ## 17 denominator df's get_Lb_ddf(fmLarge, c(0, 1)) ## 17 denominator df's # Notice: The restriction matrix L corresponding to the test above # can be found with L <- model2restriction_matrix(fmLarge, fmSmall) L
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