library(psych)
install.packages("psych")
library(sem)
ls()
data(bfi)
head(bfi)

bfi[1:5,1:2]

bfi[,1:25]		# výběr dat

BF.upr<-na.omit(bfi[,1:25])	# vynechání chybějících hodnot

BF.c<-cov(BF.upr)

model.bfi<-specifyModel()
agree->A1, fa1, NA
agree->A2, fa2, NA
agree->A3, fa3, NA
agree->A4, fa4, NA
agree->A5, fa5, NA
consc->C1, fc1, NA
consc->C2, fc2, NA
consc->C3, fc3, NA
consc->C4, fc4, NA
consc->C5, fc5, NA
extra->E1, fe1, NA
extra->E2, fe2, NA
extra->E3, fe3, NA
extra->E4, fe4, NA
extra->E5, fe5, NA
neuro->N1, fn1, NA
neuro->N2, fn2, NA
neuro->N3, fn3, NA
neuro->N4, fn4, NA
neuro->N5, fn5, NA
opene->O1, fo1, NA
opene->O2, fo2, NA
opene->O3, fo3, NA
opene->O4, fo4, NA
opene->O5, fo5, NA
agree<->agree, NA, 1
consc<->consc, NA, 1
extra<->extra, NA, 1
neuro<->neuro, NA, 1
opene<->opene, NA, 1

BF.fit<-sem(model.bfi,BF.c,nrow(BF.upr))

summary(BF.fit)
stdCoef(BF.fit)
summary(BF.fit,fit.indices=c("GFI", "AGFI", "RMSEA", "NFI", "NNFI", "CFI", "RNI", "IFI", "SRMR", "AIC", "AICc", "BIC", "CAIC"))
modIndices(BF.fit)		# provést modifikaci modelu