model.matrix-methods: Design matrices for Bayes factor linear models analyses.

In BayesFactor: Computation of Bayes Factors for Common Designs

Design matrices for Bayes factor linear models analyses.

Description

This function returns the design matrix used for computation of the Bayes factor for the numerator of a BFBayesFactor object. There must not be more than one numerator in the BFBayesFactor object.

Usage

## S4 method for signature 'BFBayesFactor'
model.matrix(object, ...)

## S4 method for signature 'BFBayesFactorTop'
model.matrix(object, ...)

Arguments

object	a BayesFactor object with a single numerator
...	arguments passed to and from related methods

Value

Returns the design matrix for the corresponding model. The 'gMap' attribute of the returned matrix contains the mapping from columns of the design matrix to g parameters

References

Rouder, J. N., Morey, R. D., Speckman, P. L., Province, J. M., (2012) Default Bayes Factors for ANOVA Designs. Journal of Mathematical Psychology. 56. p. 356-374.

Examples

## Gets the design matrix for a simple analysis
data(sleep)

bf = anovaBF(extra ~ group + ID, data = sleep, whichRandom="ID", progress=FALSE)
X = model.matrix(bf)

## Show dimensions of X (should be 20 by 12)
dim(X)

BayesFactor documentation built on Sept. 22, 2023, 1:06 a.m.