kva<-read.delim("kvadry.txt",dec=",",head=T)
kva
names(kva)
head(kva)
class(kva)
summary(kva)

install.packages("psych")
library(psych)
help(psych)

# Hlavní komponenty

pro.pc<-na.omit(kva[,5:16])
kva.pc<-princomp(pro.pc,cor=T)
summary(kva.pc)   # rozptyl
kva.pc[1]
kva.pc[2]
kva.pc[3]
kva.pc[4]
kva.pc[5]
kva.pc[6]
kva.pc[7]
loadings(kva.pc)  # náboje
plot(kva.pc,type="lines")   # scree plot 

# PCA s VARIMAXem

install.packages("GPArotation")
library(GPArotation)

?principal
kva.pc.var<-principal(pro.pc,nfactors=3,rotate="varimax")
kva.pc.var   # print results
data()


names(bfi)
bfi.pro.pc<-na.omit(bfi[,1:25])
bfi.pc.var<-principal(bfi.pro.pc,nfactors=5,rotate="varimax")
bfi.pc.var

data()

bf<-bfi
head(bf)
bf.pro.cfa<-na.omit(bf[,1:25])

install.packages("lavaan")
library(lavaan)

bf.model.lav <- ' 
agree =~ A1 + A2 + A3 + A4 + A5
consc =~ C1 + C2 + C3 + C4 + C5
extra =~ E1 + E2 + E3 + E4 + E5
neuro =~ N1 + N2 + N3 + N4 + N5
opene =~ O1 + O2 + O3 + O4 + O5
'			# specifikace modelu

bf.cfa<-cfa(bf.model.lav,data=bf.pro.cfa)
bf.cfa
class(bf.cfa)
summary(bf.cfa)

summary(bf.cfa,fit.measures=T)

fitMeasures(bf.cfa,fit.measures="all",baseline.model=NULL)

summary(bf.cfa,standardized=T)

modindices(bf.cfa)