En esta página iremos depositando el acceso a aquellos recursos que en nuestro camino de aprendizaje, creamos interesantes para conocer el apasionante mundo de la modelización SEM / PLS/ LAVAAN / ...
Colección de recursos sobre SEM (Patrick Sturgis)
Sturgis, P. (2020) Structural Equation Modelling (SEM): What it is and what it isn't. National Centre for Research Methods online learning resource. Available at https://www.ncrm.ac.uk/resources/online/SEM2016/ [ accessed: January 11, 2020]
The lavaan package is developed to provide useRs, researchers and teachers a free open-source, but commercial-quality package for latent variable modeling. You can use lavaan to estimate a large variety of multivariate statistical models, including path analysis, confirmatory factor analysis, structural equation modeling and growth curve models.
The official reference to the lavaan package is the following paper:
Yves Rosseel (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. URL http://www.jstatsoft.org/v48/i02/
Trabajando un poco sobre una escala de actitud hacia la tecnología, testando los conocimientos adquiridos en CFA. Este fue el script usado:
Referencias que deberían cumplirse:
Chi Square, no significativo
CFI > 095
TLI > 0.90
SRMR < 0.08
RMSEA entre [0.05 , 0.08]
attach(data)
model <- '
eff =~ EFF1 + EFF3 + EFF5 + EFF6 + EFF8
sys =~ SYS1 + SYS3 + SYS4
ful =~ FUL1 + FUL3 + FUL5
res =~ RES3 + RES4 + RES 5
com =~ COM1 + COM2 + COM3
con =~ CON1 + CON2 + CON3
prvl =~ PRVL1 + PRVL2 + PRVL3 + PRVL4
loy =~ LOY1 + LOY2 + LOY3 + LOY4
'
fit <- cfa(model, data, std.lv =TRUE, mimic = 'eqs', estimator = 'ML', warn = TRUE, verbose = TRUE)
summary(fit, fit.measures= TRUE, standardized = TRUE, rsquare = TRUE)
resid(fit, type='cor')
modindices(fit, sort = TRUE, minimum.value = 3.84)