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)
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)
efaModel(nFactors, variables)
Arguments
nFactors: Number of latent factors to generate.
variables: Names of variables to be used as indicators
Returns
model Full EFA model parameters.
Examples
## Not run: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 resultsmod = 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 applicationsreg.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## End(Not run)