sat-modcomp | R Documentation |
An approximate F-test based on the Satterthwaite approach.
SATmodcomp( largeModel, smallModel, details = 0, eps = sqrt(.Machine$double.eps) ) ## S3 method for class 'lmerMod' SATmodcomp( largeModel, smallModel, details = 0, eps = sqrt(.Machine$double.eps) )
largeModel |
An |
smallModel |
An |
details |
If larger than 0 some timing details are printed. |
eps |
A small number. |
Notice: It cannot be guaranteed that the results agree with other implementations of the Satterthwaite approach!
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/
getKR
, lmer
, vcovAdj
,
PBmodcomp
(fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)) L1 <- cbind(0,1) SATmodcomp(fm1, L1) (fm2 <- lmer(Reaction ~ Days + I(Days^2) + (Days|Subject), sleepstudy)) ## Test for no effect of Days. There are three ways of using the function: ## 1) Define 2-df contrast - since L has 2 (linearly independent) rows ## the F-test is on 2 (numerator) df: L2 <- rbind(c(0, 1, 0), c(0, 0, 1)) SATmodcomp(fm2, L2) ## 2) Use two model objects fm3 <- update(fm2, ~. - Days - I(Days^2)) SATmodcomp(fm2, fm3) ## 3) Specify restriction as formula SATmodcomp(fm2, ~. - Days - I(Days^2))
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