get_ddf_Lb {pbkrtest} | R Documentation |
Get adjusted denomintor degress 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) Lb_ddf(L, V0, Vadj) get_ddf_Lb(object, Lcoef) ## S3 method for class 'lmerMod' get_ddf_Lb(object, Lcoef) ddf_Lb(VVa, Lcoef, VV0 = VVa)
object |
A linear mixed model object. |
L |
A vector with the same length as |
V0, Vadj |
Unadjusted and adjusted covariance matrix for the fixed
effects parameters. Undjusted covariance matrix is obtained with
|
Lcoef |
Linear contrast matrix |
VVa |
Adjusted covariance matrix |
VV0 |
Unadjusted covariance matrix |
Adjusted degrees of freedom (adjusment 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., http://www.jstatsoft.org/v59/i09/
KRmodcomp
, vcovAdj
,
model2restrictionMatrix
,
restrictionMatrix2model
(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 <- model2restrictionMatrix(fmLarge, fmSmall) L