| efaUnrotate {semTools} | R Documentation |
This function will analyze unrotated exploratory factor analysis model. The
unrotated solution can be rotated by the orthRotate and
oblqRotate functions.
efaUnrotate(data, nf, varList = NULL, start = TRUE, aux = NULL, ...)
data |
A target |
nf |
The desired number of factors |
varList |
Target observed variables. If not specified, all variables in
|
start |
Use starting values in the analysis from the
|
aux |
The list of auxiliary variables. These variables will be included in the model by the saturated-correlates approach to account for missing information. |
... |
Other arguments in the |
This function will generate a lavaan script for unrotated exploratory factor
analysis model such that (1) all factor loadings are estimated, (2) factor
variances are fixed to 1, (3) factor covariances are fixed to 0, and (4) the
dot products of any pairs of columns in the factor loading matrix are fixed
to zero (Johnson & Wichern, 2002). The reason for creating this function
in addition to the factanal function is that users can enjoy
some advanced features from the lavaan package such as scaled
χ^2, diagonal weighted least squares for ordinal indicators, or
full-information maximum likelihood (FIML).
A lavaan output of unrotated exploratory factor analysis
solution.
Sunthud Pornprasertmanit (psunthud@gmail.com)
unrotated <- efaUnrotate(HolzingerSwineford1939, nf = 3,
varList=paste0("x", 1:9), estimator = "mlr")
summary(unrotated, std = TRUE)
inspect(unrotated, "std")
dat <- data.frame(HolzingerSwineford1939,
z = rnorm(nrow(HolzingerSwineford1939), 0, 1))
unrotated2 <- efaUnrotate(dat, nf = 2, varList = paste0("x", 1:9), aux = "z")