grt (version 0.2.1)

scale: Scale method for the class 'glc' and 'gqc'

Description

Return the discriminant scores obtained by applying the general linear classifier to the fitted data.

Usage

# S3 method for glc
scale(x, initdb = FALSE, zlimit = Inf, …)
# S3 method for gqc
scale(x, initdb = FALSE, zlimit = Inf, …)

Arguments

x

object of class glc or gqc

initdb

optional logical. If TRUE, the returned vector represents the z-scores with respect to the initial parameters, rather than the fitted parameters. Defaults to FALSE.

zlimit

optional numeric. Used to truncate the scores beyond the speficied value. Default to Inf

further arguments (currently unused)

Examples

Run this code
# NOT RUN {
data(subjdemo_2d)
fit.2dl <- glc(response ~ x + y, data=subjdemo_2d, 
    category=subjdemo_2d$category, zlimit=7)
scale(fit.2dl)

fit.2dq <- gqc(response ~ x + y, data=subjdemo_2d, 
    category=subjdemo_2d$category, zlimit=7)
scale(fit.2dq)


# }
# NOT RUN {
#plots using the discriminant scores
require(Hmisc)
options(digits=3)
fit.2dl <- glc(response ~ x + y, data=subjdemo_2d, 
    category=subjdemo_2d$category, zlimit=7)
# z-scores based on the initial decision bound
# split by the true category membership
zinit <- split(scale(fit.2dl, initdb=TRUE), subjdemo_2d$category)
histbackback(zinit)

# z-scores based on the fitted decision bound
# split by the participants' response
zfit1 <- split(scale(fit.2dl, initdb=FALSE), subjdemo_2d$category)
histbackback(zfit1)

# z-scores based on the fitted decision bound
# split by the true category membership
zfit2 <- split(scale(fit.2dl, initdb=FALSE), subjdemo_2d$response)
histbackback(zfit2)
# }

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