Q Methodology: Procrustes rotation of loadings
This is a wrap of procrustes
rotation from GPArotation for bootstrapping Q methodology in the function qmboots
.
qpcrustes(loa, target, nfactors)
loa |
factor loadings from the analysis of a resample. |
target |
factor loadings from the analysis of a subsample. |
nfactors |
fumber of factors |
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.
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")
Aiora Zabala
Zabala, Pascual (2016) Bootstrapping Q Methodology to Improve the Understanding of Human Perspectives. PLoS ONE 11(2): e0148087.
Function procrustes
from GPArotation package.
# 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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