Initial Extraction of the Components
Jogglew01NeupsyPCA<-principal(Jogglew01Neupsy,nfactors=21,rotate="none")
principal(r=Jogglew01Neupsy,nfactors=21,rotate="none")
Eigen Values
ev <- eigen(cor(Jogglew01Neupsy))
ev
Scree Plot
ap <- parallel(subject=nrow(Jogglew01Neupsy),var=ncol(Jogglew01Neupsy), rep=100,cent=.05)
nS <- nScree(x=ev$values, aparallel=ap$eigen$qevpea)
plotnScree(nS)
Rotation to Final Solution
Jogglew01NeupsyPCA.r<-principal(Jogglew01Neupsy,nfactors=3,rotate="varimax",scores=T)
principal(r=Jogglew01Neupsy,nfactors=3,rotate="varimax",scores=T)
## Principal Components Analysis
## Call: principal(r = Jogglew01Neupsy, nfactors = 3, rotate = "varimax",
## scores = T)
## Standardized loadings (pattern matrix) based upon correlation matrix
## RC1 RC2 RC3 h2 u2
## BARTaccuracy1 0.35 0.20 0.09 0.170 0.830
## DSSTefficiency1 0.73 0.25 -0.10 0.610 0.390
## LOTefficiency1 0.55 0.47 -0.09 0.526 0.474
## PVTefficiency1 0.33 0.41 -0.17 0.306 0.694
## AMefficiency1 0.50 -0.09 -0.11 0.274 0.726
## NBACKaccuracy1 0.29 -0.08 -0.03 0.094 0.906
## VOLTefficiency1 0.70 -0.09 -0.05 0.495 0.505
## MPTspeed1 0.61 0.11 -0.11 0.397 0.603
## BVRtot1 -0.46 -0.50 0.21 0.506 0.494
## CrdRot1 0.42 0.52 -0.20 0.490 0.510
## IdentPicCor1 0.63 0.31 -0.09 0.509 0.491
## IdentPicErr1 0.12 -0.32 -0.09 0.125 0.875
## CVLtca1 0.27 0.49 0.02 0.310 0.690
## DigitSpanFwd1 -0.05 0.56 -0.19 0.354 0.646
## DigitSpanBck1 -0.03 0.69 -0.24 0.540 0.460
## FluencyWord1 0.31 0.40 0.16 0.284 0.716
## TrailsAtestSec1 -0.48 -0.13 0.28 0.327 0.673
## TrailsBminusA1 -0.17 -0.13 0.93 0.918 0.082
## TrailsBtestSec1 -0.20 -0.14 0.94 0.937 0.063
## Attention1 0.05 0.47 -0.30 0.311 0.689
## ClockTotal1 0.06 0.49 0.00 0.243 0.757
##
## RC1 RC2 RC3
## SS loadings 3.55 2.96 2.22
## Proportion Var 0.17 0.14 0.11
## Cumulative Var 0.17 0.31 0.42
## Proportion Explained 0.41 0.34 0.25
## Cumulative Proportion 0.41 0.75 1.00
##
## Test of the hypothesis that 3 components are sufficient.
##
## The degrees of freedom for the null model are 210 and the objective function was NaN
## The degrees of freedom for the model are 150 and the objective function was 33.7
## The total number of observations was 293 with MLE Chi Square = 9508 with prob < 0
##
## Fit based upon off diagonal values = 0.92