regsem (version 1.9.5)

efaModel: Generates an EFA model to be used by lavaan and regsem Function created by Florian Scharf for the paper Should regularization replace simple structure rotation in Exploratory Factor Analysis -- Scharf & Nestler (in press at SEM)

Description

Generates an EFA model to be used by lavaan and regsem Function created by Florian Scharf for the paper Should regularization replace simple structure rotation in Exploratory Factor Analysis -- Scharf & Nestler (in press at SEM)

Usage

efaModel(nFactors, variables)

Value

model Full EFA model parameters.

Arguments

nFactors

Number of latent factors to generate.

variables

Names of variables to be used as indicators

Examples

if (FALSE) {
HS <- data.frame(scale(HolzingerSwineford1939[,7:15]))
# Note to find number of factors, recommended to use
# fa.parallel() from the psych package
# using the wrong number of factors can distort the results
mod = efaModel(3, colnames(HS))

semFit = sem(mod, data = HS, int.ov.free = FALSE, int.lv.free = FALSE,
            std.lv = TRUE, std.ov = TRUE, auto.fix.single = FALSE, se = "none")

# note it requires smaller penalties than other applications
reg.out2 = cv_regsem(model = semFit, pars_pen = "loadings",
                    mult.start = TRUE, multi.iter = 10,
                    n.lambda = 100, type = "lasso", jump = 10^-5, lambda.start = 0.001)
reg.out2
plot(reg.out2) # note that the solution jumps around -- make sure best fit makes sense
}