qgraph.efa {qgraph} | R Documentation |
This function performs an Exploratory Factor Analysis (EFA) using the factanal
(stats) function and sends the acquired factor loadings to qgraph.loadings
.
qgraph.efa(dat,factors=1,...,rotation="promax",residuals=TRUE, factorCors=NULL,scores="regression", corMat=nrow(dat)==ncol(dat) && all(dat==t(dat)))
dat |
A correlation matrix, data matrix or a "factanal" object |
factors |
The number of factors to extract |
rotation |
rotation to be used. Can be "varimax", "promax" or "none" |
residuals |
Logical indicating if residuals should be plotted. Defaults to TRUE |
factorCors |
Logical indicating if correlations of factors should be extracted and plotted. Defaults to FALSE if a correlation matrix is used and TRUE if a data matrix is used. |
... |
arguments passed to |
scores |
Method used to extract scores in |
corMat |
Logical indicating if the 'dat' object is a correlation matrix (TRUE) or data matrix (FALSE) |
Sacha Epskamp (s.epskamp@uva.nl)
https://sites.google.com/site/qgraphproject
qgraph
qgraph.pca
qgraph.loadings
data(big5) data(big5groups) qgraph.efa(big5,5,groups=big5groups,rotation="promax",minimum=0.2,cut=0.4, vsize=c(1,15),borders=FALSE,asize=0.07,esize=4,vTrans=200) # Tree layout: qgraph.efa(big5,5,groups=big5groups,rotation="promax",minimum=0.2,cut=0.4, vsize=c(1,15),borders=FALSE,asize=0.07,esize=4,layout="tree",width=20,filetype="R")