faSort: Sort a factor loadings matrix

In fungible: Psychometric Functions from the Waller Lab

Sort a factor loadings matrix

Description

faSort takes an unsorted factor pattern or structure matrix and returns a sorted matrix with (possibly) reflected columns. Sorting is done such that variables that load on a common factor are grouped together for ease of interpretation.

Usage

faSort(fmat, phi = NULL, BiFactor = FALSE, salient = 0.25, reflect = TRUE)

Arguments

fmat	factor loadings (pattern or structure) matrix.
phi	factor correlation matrix. Default = NULL. If reflect = TRUE then phi will be corrected to match the new factor orientations.
BiFactor	(logical) Is the solution a bifactor model?
salient	factor markers with loadings >= abs(salient) will be saved in the markers list. Note that a variable can be a marker of more than one factor.
reflect	(logical) if reflect = TRUE then the factors will be reflected such that salient loadings are mostly positive. Default Reflect = TRUE.

Value

loadings	sorted factor loadings matrix.
phi	reflected factor correlation matrix when phi is given as an argument.
markers	A list of factor specific markers with loadings >= abs(salient). Markers are sorted by the absolute value of the salient factor loadings.
sortOrder	sorted row numbers.
SEmat	The SEmat is a so-called Start-End matrix that lists the first (start) and last (end) row for each factor in the sorted pattern matrix.

Author(s)

Niels Waller

See Also

fals

Other Factor Analysis Routines: BiFAD(), Box26, GenerateBoxData(), Ledermann(), SLi(), SchmidLeiman(), faAlign(), faEKC(), faIB(), faLocalMin(), faMB(), faMain(), faScores(), faStandardize(), faX(), fals(), fapa(), fareg(), fsIndeterminacy(), orderFactors(), print.faMB(), print.faMain(), promaxQ(), summary.faMB(), summary.faMain()

Examples

set.seed(123)
F <- matrix( c( .5,  0, 
                .6,  0,
                 0, .6,
                .6,  0,
                 0, .5,
                .7,  0,
                 0, .7,
                 0, .6), nrow = 8, ncol = 2, byrow=TRUE)

Rex1 <- F %*% t(F); diag(Rex1) <- 1

Items <- c("1. I am often tense.\n",
           "2. I feel anxious much of the time.\n",
           "3. I am a naturally curious individual.\n",
           "4. I have many fears.\n",
           "5. I read many books each year.\n",
           "6. My hands perspire easily.\n",
           "7. I have many interests.\n",
           "8. I enjoy learning new words.\n")

exampleOut <- fals(R = Rex1, nfactors = 2)

# Varimax rotation
Fload <- varimax(exampleOut$loadings)$loadings[]

# Add some row labels
rownames(Fload) <- paste0("V", 1:nrow(Fload))

cat("\nUnsorted fator loadings\n")
print(round( Fload, 2) )

# Sort items and reflect factors
out1 <- faSort(fmat = Fload, 
               salient = .25, 
               reflect = TRUE)
               
FloadSorted <- out1$loadings

cat("\nSorted fator loadings\n")
print(round( FloadSorted, 2) )

# Print sorted items
cat("\n Items sorted by Factor\n")
cat("\n",Items[out1$sortOrder])

fungible documentation built on May 29, 2024, 8:28 a.m.