psych (version 2.6.1)

bassAckward: The Bass-Ackward factoring algorithm discussed by Goldberg

Description

Goldberg (2006) described a hierarchical factor structure organization from the ``top down". The original idea was to do successive factor analyses from 1 to nf factors organized by factor score correlations from one level to the next. Waller (2007) discussed a simple way of doing this for components without finding the scores. Using the factor correlations (from Gorsuch) to organize factors hierarchically results may be organized at many different levels. The algorithm may be applied to principal components (pca) or to true factor analysis.

Usage

bassAckward(r, nfactors = 1, fm = "minres", rotate = "oblimin", scores = "tenBerge",
   adjust=TRUE, plot=TRUE,cut=.3, use = "pairwise", cor = "cor", weight = NULL,
   correct = 0.5,...)
bassAckward.diagram(x,digits=2,cut = .3,labels=NULL,marg=c(1.5,.5,1.0,.5),
   main="BassAckward",items=TRUE,sort=TRUE,lr=TRUE,curves=FALSE,organize=TRUE,
   values=FALSE,...)

Value

Call

Echo the call

fm

Echos the factor method used

fa

A list of the factor loadings at each level

bass.ack

A list of the factor correlations at each level

summary

The factors at each level

sumnames

Summary of the factor names

labels

Factor labels including items for each level

r

The correlation matrix analyzed

Phi

The factor correlations at each level

fa

The factor analysis loadings at each level, now includes Phi values

fa.vac

The variance accounted for by each factor at each level

Details

This is essentially a wrapper to the fa and pca combined with the faCor functions. They are called repeatedly and then the weights from the resulting solutions are used to find the factor/component correlations.

Although the default is do all factor solutions from 1 to the nfactors, this can be simplified by specifying just some of the factor solutions. Thus, for the 135 items of the spi, it is more reasonable to ask for 3,5, and 27 item solutions.

The function bassAckward.diagram may be called using the diagram function or may be called directly.

The output from bassAckward.diagram is the sorted factor structure suitable for using fa.lookup.

Although not particularly pretty, it is possible to do Schmid-Leiman rotations at each level. Specify the rotation as rotate="schmid".

References

Goldberg, L.R. (2006) Doing it all Bass-Ackwards: The development of hierarchical factor structures from the top down. Journal of Research in Personality, 40, 4, 347-358.

Gorsuch, Richard, (1983) Factor Analysis. Lawrence Erlebaum Associates.

Revelle, William. (in prep) An introduction to psychometric theory with applications in R. Springer. Working draft available at https://personality-project.org/r/book/

Waller, N. (2007), A general method for computing hierarchical component structures by Goldberg's Bass-Ackwards method, Journal of Research in Personality, 41, 4, 745-752, DOI: 10.1016/j.jrp.2006.08.005

See Also

fa, pca, omega and iclust for alternative hierarchical solutions. link{fa.lookup} to show the items in the lowest level of the solution.

Examples

bassAckward(Thurstone,4,main="Thurstone data set")
f.labels <- list(level1=cs(Approach,Avoid),level2=cs(PosAffect,NegAffect,Constraint), 
level3 = cs(Extraversion,Agreeableness,Neuroticism,Conscientiousness,Openness))

ba <- bassAckward(bfi[1:25],c(2,3,5),labels=f.labels,
        main="bfi data set from psychTools", values=TRUE)
print(ba,short=FALSE)
#show the items associated with the 5 level solution
fa.lookup(ba,dictionary=bfi.dictionary)
#now show the items associated with the 3 level solution
fa.lookup(ba$fa[[2]],dictionary=bfi.dictionary)
# compare the 3 factor solution to what get by extracting 3 factors directly
f3 <- fa(bfi[1:25],3)
f3$loadings - ba$fa[[2]]$loadings   # these are the same
 #do pca instead of factors  just summarize, don't plot
summary(bassAckward(bfi[1:25],c(1,3,5,7),fm="pca",
       main="Components",plot=FALSE))
##not run, but useful example
# \donttest{  
f.labels <- list(level1 = cs(Neg,Pos,Constrain),level2 = cs(Extra,Neuro,Cons,Open,Agree),
level3 = cs(attnseeking,sociability,impulsivity,
   charisma,sensationseek,emotexpr,humor,anxiety,
   emotstab,irritability,wellbeing,industry,order,author,honesty,perfect,easygoing,
   selfcontrol,conservatism,creativity,introspect,art,
   intellect,conform,adaptability,compassion,trust))
if(require("psychTools") ) {
sp5 <- bassAckward(psychTools::spi[11:145], c(3,5,27),labels=f.labels,
           main="spi data set from psychTools")}
# }