data(msq)
#basic descriptive statistics
describe(msq)
#score them for 12 short scales
keys <- make.keys(75,list(
EA=c(1, 26, 69, 70, 72, 31, 44, -57,-65,-23),
TA =c(40,43,29, 64, 16, -51, -61,-47, -14, -10),
PA =c(1,28,62, 39, 21, 11, 41, 27, 49, 3),
NAf =c(43,46, 55, 2, 34, 7, 22,68,36, 42),
HAct = c(1,6, 63, 40, 8),
aPA = c(25, 28, 27,44),
uNA = c(14, 56, 52, 10, 18, 9),
pa = c(35,71,48, 15, 19 ),
LAct = c(51, 38, 37, 61, 66),
uPA =c(24, 13, 58, 65, 23),
naf = c(53, 12, 67, 32, 33),
aNA = c(43, 5, 46, 29, 22))
)
rownames(keys) <- colnames(msq)[1:75]
msq.scores <- score.items(keys,msq[1:75])
#show a circumplex structure
fcirc <- fa(msq.scores$scores[,5:12],2)
fa.plot(fcirc,labels=colnames(msq.scores$scores)[5:12])
#extend this solution to EA/TA NA/PA space
fe <- fa.extension(cor(msq.scores$scores[,5:12],msq.scores$scores[,1:4]),fcirc)
fa.diagram(fcirc,fe=fe,main="Extending the circumplex structure to EA/TA and PA/NA ")
#show the 2 dimensional structure
f2 <- fa(msq[1:70],2)
fa.plot(f2,labels=colnames(msq)[1:70],title="2 dimensions of affect")
#sort them by polar coordinates
round(polar(f2),2)
Run the code above in your browser using DataLab