model-coerce {pbkrtest} | R Documentation |
Testing a small model under a large model corresponds imposing restrictions on the model matrix of the larger model and these restrictions come in the form of a restriction matrix. These functions converts a model to a restriction matrix and vice versa.
model2restrictionMatrix(largeModel, smallModel) ## S3 method for class 'merMod' model2restrictionMatrix(largeModel, smallModel) ## S3 method for class 'lm' model2restrictionMatrix(largeModel, smallModel) restrictionMatrix2model(largeModel, LL) ## S3 method for class 'merMod' restrictionMatrix2model(largeModel, LL) ## S3 method for class 'lm' restrictionMatrix2model(largeModel, LL)
largeModel, smallModel |
Model objects of the same "type". Possible types are linear mixed effects models and linear models (including generalized linear models) |
LL |
A restriction matrix. |
model2restrictionMatrix
: A restriction matrix.
restrictionMatrix2model
: A model object.
That these functions are visible is a recent addition; minor changes may occur.
Ulrich Halekoh uhalekoh@health.sdu.dk, 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/
PBmodcomp
, PBrefdist
,
KRmodcomp
library(pbkrtest) data("beets", package = "pbkrtest") sug <- lm(sugpct ~ block + sow + harvest, data=beets) sug.h <- update(sug, .~. - harvest) sug.s <- update(sug, .~. - sow) ## Construct restriction matrices from models L.h <- model2restrictionMatrix(sug, sug.h); L.h L.s <- model2restrictionMatrix(sug, sug.s); L.s ## Construct submodels from restriction matrices mod.h <- restrictionMatrix2model(sug, L.h); mod.h mod.s <- restrictionMatrix2model(sug, L.s); mod.s ## The models have the same fitted values plot(fitted(mod.h), fitted(sug.h)) plot(fitted(mod.s), fitted(sug.s)) ## and the same log likelihood logLik(mod.h) logLik(sug.h) logLik(mod.s) logLik(sug.s)