pbkrtest (version 0.5.3)

model-coerce: Conversion between a model object and a restriction matrix

Description

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.

Usage

model2restriction_matrix(largeModel, smallModel, sparse = FALSE)
restriction_matrix2model(largeModel, L, REML = TRUE, ...)
make_model_matrix(X, L)
make_restriction_matrix(X, X2)

Value

model2restriction_matrix: A restriction matrix. restriction_matrix2model: A model object.

Arguments

largeModel, smallModel

Model objects of the same "type". Possible types are linear mixed effects models and linear models (including generalized linear models)

sparse

Should the restriction matrix be sparse or dense?

L

A restriction matrix; a full rank matrix with as many columns as X has.

REML

Controls if new model object should be fitted with REML or ML.

...

Additional arguments; not used.

X, X2

Model matrices. Must have same number of rows.

Author

Ulrich Halekoh , Søren Højsgaard

Details

make_restriction_matrix Make a restriction matrix. If span(X2) is in span(X) then the corresponding restriction matrix L is returned.

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

PBmodcomp, PBrefdist, KRmodcomp

Examples

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 <- model2restriction_matrix(sug, sug.h); L.h
L.s <- model2restriction_matrix(sug, sug.s); L.s

## Construct submodels from restriction matrices
mod.h <- restriction_matrix2model(sug, L.h); mod.h
mod.s <- restriction_matrix2model(sug, L.s); mod.s

## Sanity check: The models have the same fitted values and log likelihood
plot(fitted(mod.h), fitted(sug.h))
plot(fitted(mod.s), fitted(sug.s))
logLik(mod.h)
logLik(sug.h)
logLik(mod.s)
logLik(sug.s)