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

model2restrictionMatrix(largeModel, smallModel)
restrictionMatrix2model(largeModel, LL)

Arguments

largeModel, smallModel

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

A restriction matrix.

Value

model2restrictionMatrix: A restriction matrix. restrictionMatrix2model: A model object.

References

Ulrich Halekoh, S<U+00F8>ren H<U+00F8>jsgaard (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/

Examples

Run this code

# NOT RUN {
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)

# }

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