# Options

# Surpress scientific notations, digits and lines

options(scipen=999, digits=10, max.print=99999999)



# PPT data R EFA

library(psych)

# PAF

PAF<-fa(Data.01.PPT[,1:12], fm="pa", nfactors=4, rotate="promax")
PAF

cortest.bartlett(cor(Data.01.PPT[,1:12]), n=439)

# cortest.bartlett(Data.01.PPT[,1:12])

KMO(Data.01.PPT[,1:12])



# Scree plot

PAF00<-fa(Data.01.PPT[,1:12], fm="pa", nfactors=4, SMC=TRUE, rotate="none")
PAF00

plot(PAF00$e.values)

scree(Data.01.PPT[,1:12])

VSS.scree(Data.01.PPT[,1:12])

# PC

PC<-principal(Data.01.PPT[,1:12], nfactors=4, rotate="promax")
PC

# Parallel Analysis and MAP test

fa.parallel(Data.01.PPT[,1:12], fa="both")
            
vss(Data.01.PPT[,1:12], n=12, rotate="none")

# ML EFA

ML<-factanal(Data.01.PPT[,1:12], factors=4, rotation="promax")
ML

# Schmid Leiman Solution

SL<-schmid(Data.01.PPT[,1:12], fm="pa", nfactors=4, rotate="promax")
SL


# Coefficient Alpha

alpha(Data.01.PPT[,1:3])