Q Methodology: Procrustes rotation of loadings

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Description

This is a wrap of procrustes rotation from GPArotation for bootstrapping Q methodology in the function qmboots.

Usage

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qpcrustes(loa, target, nfactors)

Arguments

loa

factor loadings from the analysis of a resample.

target

factor loadings from the analysis of a subsample.

nfactors

fumber of factors

Details

Returns the factor loadings for the subsample after applying Procrustes rotation to correct the indeterminacy issue. Use procrustes from GPArotation. Used within the function qmboots, not intended for independent use.

Note

this function is called within the function qmboots. Not intended to be used separately. The function calls procrustes from GPArotation, a package that requires the package graph. As from April 2016 the package has been moved to Bioconductor, and therefore it needs to be installed manually. If you get errors of missing packages when using this function or qmboots, install graph manually: source("https://bioconductor.org/biocLite.R") biocLite("graph")

Author(s)

Aiora Zabala

References

Zabala, Pascual (2016) Bootstrapping Q Methodology to Improve the Understanding of Human Perspectives. PLoS ONE 11(2): e0148087.

See Also

Function procrustes from GPArotation package.

Examples

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# This example requires installing 'MCMCpack', check warning when running line 10 below:
data(lipset)
qm <- qmethod(lipset[[1]], nfactors=3, rotation="varimax")
qselim <- sample(1:3, 2, replace=FALSE) ##q sorts to eliminate
subdata <- lipset[[1]][ , -qselim]
library(psych)
loa <- as.data.frame(unclass(principal(subdata, 
         nfactors=3, rotate="varimax")$loadings))
target <- as.matrix(as.data.frame(qm[3]))
colnames(target) <- paste("target_f", 1:3, sep="")
subtarget <- target[c(-qselim),]
# qindt <- qpcrustes(loa, subtarget, 3)
# qindt

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