Initial Extraction of the Components
Jogglew03NeupsyPCA<-principal(Jogglew03Neupsy,nfactors=16,rotate="none")
principal(r=Jogglew03Neupsy,nfactors=16,rotate="none")
Eigen Values
ev <- eigen(cor(Jogglew03Neupsy))
ev
Scree Plot
ap <- parallel(subject=nrow(Jogglew03Neupsy),var=ncol(Jogglew03Neupsy), rep=100,cent=.05)
nS <- nScree(x=ev$values, aparallel=ap$eigen$qevpea)
plotnScree(nS)
Rotation to Final Solution
Jogglew03NeupsyPCA.r<-principal(Jogglew03Neupsy,nfactors=5,rotate="promax",scores=T)
principal(r=Jogglew03Neupsy,nfactors=5,rotate="promax",scores=T)
## Principal Components Analysis
## Call: principal(r = Jogglew03Neupsy, nfactors = 5, rotate = "promax",
## scores = T)
## Standardized loadings (pattern matrix) based upon correlation matrix
## PC1 PC2 PC3 PC4 PC5 h2 u2
## BARTaccuracy3 0.23 0.07 0.26 0.38 -0.40 0.55 0.45
## DSSTefficiency3 0.59 -0.08 0.37 0.01 0.08 0.64 0.36
## LOTefficiency3 0.81 -0.17 0.02 0.09 -0.07 0.57 0.43
## PVTefficiency3 0.67 -0.01 -0.22 0.07 0.26 0.47 0.53
## AMefficiency3 -0.17 0.08 0.79 -0.10 -0.03 0.57 0.43
## NBACKaccuracy3 -0.23 0.15 0.12 0.76 0.19 0.56 0.44
## VOLTefficiency3 0.11 -0.26 0.74 0.09 0.15 0.58 0.42
## MPTspeed3 0.68 -0.37 0.21 -0.06 0.02 0.47 0.53
## BVRtot3 -0.83 -0.03 0.33 -0.02 -0.13 0.61 0.39
## StroopColors3 0.53 0.12 0.16 -0.30 0.12 0.58 0.42
## StroopWords3 0.39 0.39 -0.06 -0.08 -0.04 0.43 0.57
## StroopMixed3 0.31 0.34 0.17 -0.12 0.09 0.46 0.54
## CVLtca3 0.01 0.30 0.37 0.12 0.44 0.52 0.48
## DigitSpanFwd3 -0.14 0.84 0.02 0.12 -0.12 0.61 0.39
## DigitSpanBck3 -0.11 0.92 -0.15 0.09 0.14 0.74 0.26
## FluencyWord3 0.14 0.02 0.09 0.16 0.76 0.64 0.36
## TrailsAtestSec3 -0.57 -0.01 -0.17 -0.04 0.03 0.46 0.54
## TrailsBtestSec3 -0.40 -0.21 -0.15 -0.09 0.14 0.40 0.60
## Attention3 0.58 0.29 -0.10 -0.20 -0.16 0.54 0.46
## ClockTotal3 0.30 0.03 -0.31 0.58 0.06 0.45 0.55
##
## PC1 PC2 PC3 PC4 PC5
## SS loadings 4.25 2.22 1.96 1.25 1.20
## Proportion Var 0.21 0.11 0.10 0.06 0.06
## Cumulative Var 0.21 0.32 0.42 0.48 0.54
## Proportion Explained 0.39 0.20 0.18 0.12 0.11
## Cumulative Proportion 0.39 0.59 0.77 0.89 1.00
##
## With component correlations of
## PC1 PC2 PC3 PC4 PC5
## PC1 1.00 0.50 0.46 0.09 0.14
## PC2 0.50 1.00 0.30 -0.06 0.11
## PC3 0.46 0.30 1.00 0.05 -0.01
## PC4 0.09 -0.06 0.05 1.00 -0.16
## PC5 0.14 0.11 -0.01 -0.16 1.00
##
## Test of the hypothesis that 5 components are sufficient.
##
## The degrees of freedom for the null model are 190 and the objective function was 5.78
## The degrees of freedom for the model are 100 and the objective function was 1.77
## The total number of observations was 229 with MLE Chi Square = 383.9 with prob < 7e-35
##
## Fit based upon off diagonal values = 0.92