PCA for Shari
Cognitive Function Variables
Initial Extraction of Exponents
## Principal Components Analysis
## Call: principal(r = CtrCogdat, nfactors = 11, rotate = "none", scores = TRUE,
## missing = TRUE, impute = "median")
## Standardized loadings (pattern matrix) based upon correlation matrix
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
## BVRtot -0.62 0.25 0.21 0.29 0.33 -0.19 0.51 0.13 -0.04 0.03
## CVLtca 0.74 0.55 0.09 -0.04 0.08 -0.02 -0.06 -0.08 -0.13 0.33
## CVLfrs 0.72 0.63 0.00 0.00 -0.01 -0.03 0.01 0.05 0.09 -0.12
## CVLfrl 0.73 0.60 0.00 -0.04 -0.03 0.02 0.06 0.10 -0.02 -0.19
## FluencyWord 0.38 -0.06 -0.58 0.63 0.22 -0.14 -0.13 -0.04 0.16 0.02
## DigitSpanBck 0.66 -0.28 0.43 0.08 -0.29 -0.24 0.13 0.01 0.36 0.07
## DigitSpanFwd 0.61 -0.34 0.40 0.36 -0.01 -0.26 -0.14 -0.08 -0.33 -0.10
## Attention 0.58 -0.27 0.28 -0.16 0.60 0.27 -0.02 -0.19 0.13 -0.05
## TrailsAtestSec -0.58 0.40 0.22 0.39 -0.22 0.27 0.02 -0.43 0.05 -0.03
## TrailsBtestSec -0.62 0.25 0.42 0.23 0.12 0.11 -0.41 0.33 0.10 0.02
## StroopMixed 0.62 -0.29 -0.02 0.31 -0.17 0.55 0.21 0.24 -0.08 0.05
## PC11 h2 u2 com
## BVRtot -0.01 1 -2.2e-16 4.1
## CVLtca 0.03 1 4.4e-16 2.5
## CVLfrs -0.24 1 0.0e+00 2.3
## CVLfrl 0.21 1 6.7e-16 2.4
## FluencyWord 0.03 1 -1.3e-15 3.3
## DigitSpanBck 0.03 1 6.7e-16 3.9
## DigitSpanFwd -0.02 1 1.2e-15 4.7
## Attention 0.01 1 0.0e+00 3.9
## TrailsAtestSec 0.01 1 1.2e-15 4.9
## TrailsBtestSec 0.01 1 1.4e-15 4.4
## StroopMixed -0.02 1 6.7e-16 3.9
##
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11
## SS loadings 4.38 1.70 1.04 0.95 0.69 0.64 0.54 0.43 0.33 0.18 0.11
## Proportion Var 0.40 0.15 0.09 0.09 0.06 0.06 0.05 0.04 0.03 0.02 0.01
## Cumulative Var 0.40 0.55 0.65 0.73 0.80 0.86 0.90 0.94 0.97 0.99 1.00
## Proportion Explained 0.40 0.15 0.09 0.09 0.06 0.06 0.05 0.04 0.03 0.02 0.01
## Cumulative Proportion 0.40 0.55 0.65 0.73 0.80 0.86 0.90 0.94 0.97 0.99 1.00
##
## Mean item complexity = 3.6
## Test of the hypothesis that 11 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0
## with the empirical chi square 0 with prob < NA
##
## Fit based upon off diagonal values = 1##
## Loadings:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9
## BVRtot -0.622 0.245 0.212 0.290 0.331 -0.188 0.510 0.127
## CVLtca 0.738 0.549 -0.134
## CVLfrs 0.721 0.630
## CVLfrl 0.735 0.599
## FluencyWord 0.383 -0.580 0.634 0.217 -0.137 -0.135 0.157
## DigitSpanBck 0.662 -0.284 0.426 -0.289 -0.236 0.127 0.362
## DigitSpanFwd 0.612 -0.343 0.402 0.363 -0.261 -0.137 -0.334
## Attention 0.577 -0.273 0.284 -0.161 0.597 0.270 -0.193 0.126
## TrailsAtestSec -0.578 0.398 0.219 0.386 -0.218 0.267 -0.432
## TrailsBtestSec -0.622 0.254 0.421 0.234 0.118 0.108 -0.414 0.331 0.101
## StroopMixed 0.615 -0.291 0.308 -0.168 0.552 0.206 0.238
## PC10 PC11
## BVRtot
## CVLtca 0.330
## CVLfrs -0.122 -0.240
## CVLfrl -0.193 0.214
## FluencyWord
## DigitSpanBck
## DigitSpanFwd
## Attention
## TrailsAtestSec
## TrailsBtestSec
## StroopMixed
##
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10
## SS loadings 4.384 1.702 1.039 0.952 0.694 0.641 0.536 0.432 0.330 0.183
## Proportion Var 0.399 0.155 0.094 0.087 0.063 0.058 0.049 0.039 0.030 0.017
## Cumulative Var 0.399 0.553 0.648 0.734 0.797 0.856 0.904 0.944 0.974 0.990
## PC11
## SS loadings 0.108
## Proportion Var 0.010
## Cumulative Var 1.000Scree Plot
## [1] 4.3836260 1.7023500 1.0391424 0.9524832 0.6938079 0.6409679 0.5359233
## [8] 0.4318366 0.3297051 0.1826104 0.1075472
Rotation to Final Solution
#Rotation with 2-factor solution
##
## Factor analysis with Call: principal(r = CtrCogdat, nfactors = 2, rotate = "promax", scores = TRUE,
## missing = TRUE, impute = "median")
##
## Test of the hypothesis that 2 factors are sufficient.
## The degrees of freedom for the model is 34 and the objective function was 0.84
## The number of observations was 238 with Chi Square = 193.68 with prob < 3e-24
##
## The root mean square of the residuals (RMSA) is 0.08
##
## With component correlations of
## RC1 RC2
## RC1 1.00 0.44
## RC2 0.44 1.00## Principal Components Analysis
## Call: principal(r = CtrCogdat, nfactors = 2, rotate = "promax", scores = TRUE,
## missing = TRUE, impute = "median")
## Standardized loadings (pattern matrix) based upon correlation matrix
## RC1 RC2 h2 u2 com
## BVRtot -0.64 -0.05 0.45 0.553 1.0
## CVLtca 0.03 0.91 0.85 0.154 1.0
## CVLfrs -0.05 0.98 0.92 0.084 1.0
## CVLfrl -0.01 0.95 0.90 0.101 1.0
## FluencyWord 0.32 0.12 0.15 0.849 1.3
## DigitSpanBck 0.71 0.03 0.52 0.480 1.0
## DigitSpanFwd 0.72 -0.05 0.49 0.508 1.0
## Attention 0.64 0.00 0.41 0.592 1.0
## TrailsAtestSec -0.75 0.12 0.49 0.507 1.1
## TrailsBtestSec -0.65 -0.04 0.45 0.549 1.0
## StroopMixed 0.68 0.00 0.46 0.537 1.0
##
## RC1 RC2
## SS loadings 3.38 2.71
## Proportion Var 0.31 0.25
## Cumulative Var 0.31 0.55
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## With component correlations of
## RC1 RC2
## RC1 1.00 0.44
## RC2 0.44 1.00
##
## Mean item complexity = 1
## Test of the hypothesis that 2 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0.08
## with the empirical chi square 179.18 with prob < 1.2e-21
##
## Fit based upon off diagonal values = 0.95##
## Loadings:
## RC1 RC2
## BVRtot -0.644
## CVLtca 0.905
## CVLfrs 0.978
## CVLfrl 0.954
## FluencyWord 0.320 0.121
## DigitSpanBck 0.706
## DigitSpanFwd 0.722
## Attention 0.638
## TrailsAtestSec -0.747 0.122
## TrailsBtestSec -0.652
## StroopMixed 0.679
##
## RC1 RC2
## SS loadings 3.391 2.725
## Proportion Var 0.308 0.248
## Cumulative Var 0.308 0.556Health Behavior Variables
Initial Extraction of Exponents
## Principal Components Analysis
## Call: principal(r = CtrHealthdat, nfactors = 5, rotate = "none", scores = TRUE,
## missing = TRUE, impute = "median")
## Standardized loadings (pattern matrix) based upon correlation matrix
## PC1 PC2 PC3 PC4 PC5 h2 u2 com
## CigaretteEver 0.75 0.00 -0.10 0.16 0.64 1 -8.9e-16 2.1
## AlcEver 0.59 -0.23 0.65 -0.42 -0.07 1 7.8e-16 3.0
## DrugUse 0.72 -0.03 0.07 0.55 -0.41 1 4.4e-16 2.5
## PSQglobal 0.06 0.97 0.25 -0.02 0.01 1 6.7e-16 1.1
## hei2010_total_score -0.62 -0.15 0.60 0.43 0.22 1 4.4e-16 3.2
##
## PC1 PC2 PC3 PC4 PC5
## SS loadings 1.82 1.01 0.85 0.69 0.63
## Proportion Var 0.36 0.20 0.17 0.14 0.13
## Cumulative Var 0.36 0.57 0.74 0.87 1.00
## Proportion Explained 0.36 0.20 0.17 0.14 0.13
## Cumulative Proportion 0.36 0.57 0.74 0.87 1.00
##
## Mean item complexity = 2.4
## Test of the hypothesis that 5 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0
## with the empirical chi square 0 with prob < NA
##
## Fit based upon off diagonal values = 1##
## Loadings:
## PC1 PC2 PC3 PC4 PC5
## CigaretteEver 0.747 0.164 0.636
## AlcEver 0.589 -0.229 0.646 -0.423
## DrugUse 0.723 0.548 -0.415
## PSQglobal 0.966 0.248
## hei2010_total_score -0.622 -0.152 0.596 0.431 0.219
##
## PC1 PC2 PC3 PC4 PC5
## SS loadings 1.820 1.010 0.848 0.692 0.630
## Proportion Var 0.364 0.202 0.170 0.138 0.126
## Cumulative Var 0.364 0.566 0.736 0.874 1.000Scree Plot
## [1] 1.8199843 1.0100661 0.8484243 0.6917252 0.6298002
Rotation to Final Solution
#Rotation with 2-factor solution
##
## Factor analysis with Call: principal(r = CtrHealthdat, nfactors = 2, rotate = "promax",
## scores = TRUE, missing = TRUE, impute = "median")
##
## Test of the hypothesis that 2 factors are sufficient.
## The degrees of freedom for the model is 1 and the objective function was 0.28
## The number of observations was 238 with Chi Square = 65.05 with prob < 7.3e-16
##
## The root mean square of the residuals (RMSA) is 0.15
##
## With component correlations of
## RC1 RC2
## RC1 1.00 0.01
## RC2 0.01 1.00## Principal Components Analysis
## Call: principal(r = CtrHealthdat, nfactors = 2, rotate = "promax",
## scores = TRUE, missing = TRUE, impute = "median")
## Standardized loadings (pattern matrix) based upon correlation matrix
## RC1 RC2 h2 u2 com
## CigaretteEver 0.75 0.02 0.56 0.441 1.0
## AlcEver 0.60 -0.21 0.40 0.600 1.2
## DrugUse 0.72 0.00 0.52 0.476 1.0
## PSQglobal 0.02 0.97 0.94 0.062 1.0
## hei2010_total_score -0.61 -0.17 0.41 0.590 1.2
##
## RC1 RC2
## SS loadings 1.82 1.01
## Proportion Var 0.36 0.20
## Cumulative Var 0.36 0.57
## Proportion Explained 0.64 0.36
## Cumulative Proportion 0.64 1.00
##
## With component correlations of
## RC1 RC2
## RC1 1.00 0.01
## RC2 0.01 1.00
##
## Mean item complexity = 1.1
## Test of the hypothesis that 2 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0.15
## with the empirical chi square 109.72 with prob < 1.1e-25
##
## Fit based upon off diagonal values = 0.5##
## Loadings:
## RC1 RC2
## CigaretteEver 0.747
## AlcEver 0.600 -0.207
## DrugUse 0.724
## PSQglobal 0.968
## hei2010_total_score -0.614 -0.175
##
## RC1 RC2
## SS loadings 1.818 1.011
## Proportion Var 0.364 0.202
## Cumulative Var 0.364 0.566Cardiometabolic Risk Factors
Initial Extraction of Exponents
## Principal Components Analysis
## Call: principal(r = CtrCRFdat, nfactors = 8, rotate = "none", scores = TRUE,
## missing = TRUE, impute = "median")
## Standardized loadings (pattern matrix) based upon correlation matrix
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 h2 u2 com
## BPsitMeanDia 0.73 -0.50 -0.04 0.15 -0.04 0.03 -0.29 0.32 1 1.1e-16 2.7
## BPsitMeansys 0.82 -0.41 -0.09 0.07 -0.02 0.03 -0.10 -0.37 1 2.1e-15 2.0
## HgbA1C 0.35 0.52 0.44 -0.34 0.35 0.05 -0.42 -0.02 1 5.6e-16 5.4
## Chol 0.16 -0.12 0.85 0.40 -0.02 0.01 0.28 0.01 1 2.1e-15 1.8
## BMI 0.55 0.41 -0.16 0.20 0.09 -0.66 0.13 0.03 1 1.9e-15 3.2
## CRP 0.13 0.51 -0.28 0.69 0.13 0.39 -0.06 -0.01 1 -2.2e-16 3.1
## IMTmean 0.43 0.46 0.07 -0.18 -0.74 0.12 0.01 0.02 1 1.0e-15 2.6
## PWV 0.64 0.07 -0.14 -0.38 0.29 0.29 0.50 0.08 1 1.6e-15 3.7
##
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## SS loadings 2.28 1.35 1.05 0.99 0.79 0.69 0.62 0.25
## Proportion Var 0.28 0.17 0.13 0.12 0.10 0.09 0.08 0.03
## Cumulative Var 0.28 0.45 0.58 0.71 0.81 0.89 0.97 1.00
## Proportion Explained 0.28 0.17 0.13 0.12 0.10 0.09 0.08 0.03
## Cumulative Proportion 0.28 0.45 0.58 0.71 0.81 0.89 0.97 1.00
##
## Mean item complexity = 3.1
## Test of the hypothesis that 8 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0
## with the empirical chi square 0 with prob < NA
##
## Fit based upon off diagonal values = 1##
## Loadings:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## BPsitMeanDia 0.733 -0.499 0.150 -0.289 0.319
## BPsitMeansys 0.823 -0.405 -0.368
## HgbA1C 0.346 0.522 0.438 -0.335 0.353 -0.418
## Chol 0.164 -0.115 0.848 0.402 0.281
## BMI 0.548 0.414 -0.163 0.203 -0.658 0.134
## CRP 0.128 0.510 -0.275 0.690 0.134 0.388
## IMTmean 0.428 0.462 -0.178 -0.743 0.124
## PWV 0.644 -0.143 -0.376 0.285 0.285 0.498
##
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## SS loadings 2.276 1.350 1.047 0.992 0.786 0.686 0.617 0.245
## Proportion Var 0.285 0.169 0.131 0.124 0.098 0.086 0.077 0.031
## Cumulative Var 0.285 0.453 0.584 0.708 0.806 0.892 0.969 1.000Scree Plot
## [1] 2.2761408 1.3502587 1.0471759 0.9916668 0.7862415 0.6864357 0.6167865
## [8] 0.2452941
Rotation to Final Solution
#Rotation with 2-factor solution
##
## Factor analysis with Call: principal(r = CtrCRFdat, nfactors = 2, rotate = "promax", scores = TRUE,
## missing = TRUE, impute = "median")
##
## Test of the hypothesis that 2 factors are sufficient.
## The degrees of freedom for the model is 13 and the objective function was 0.39
## The number of observations was 238 with Chi Square = 91.48 with prob < 7.3e-14
##
## The root mean square of the residuals (RMSA) is 0.12
##
## With component correlations of
## RC1 RC2
## RC1 1.00 0.24
## RC2 0.24 1.00## Principal Components Analysis
## Call: principal(r = CtrCRFdat, nfactors = 2, rotate = "promax", scores = TRUE,
## missing = TRUE, impute = "median")
## Standardized loadings (pattern matrix) based upon correlation matrix
## RC1 RC2 h2 u2 com
## BPsitMeanDia 0.90 -0.08 0.79 0.21 1.0
## BPsitMeansys 0.90 0.05 0.84 0.16 1.0
## HgbA1C -0.10 0.64 0.39 0.61 1.1
## Chol 0.20 -0.02 0.04 0.96 1.0
## BMI 0.13 0.65 0.47 0.53 1.1
## CRP -0.26 0.52 0.28 0.72 1.5
## IMTmean 0.00 0.63 0.40 0.60 1.0
## PWV 0.43 0.39 0.42 0.58 2.0
##
## RC1 RC2
## SS loadings 1.96 1.66
## Proportion Var 0.25 0.21
## Cumulative Var 0.25 0.45
## Proportion Explained 0.54 0.46
## Cumulative Proportion 0.54 1.00
##
## With component correlations of
## RC1 RC2
## RC1 1.00 0.24
## RC2 0.24 1.00
##
## Mean item complexity = 1.2
## Test of the hypothesis that 2 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0.12
## with the empirical chi square 177.71 with prob < 5e-31
##
## Fit based upon off diagonal values = 0.71##
## Loadings:
## RC1 RC2
## BPsitMeanDia 0.903
## BPsitMeansys 0.905
## HgbA1C -0.104 0.643
## Chol 0.204
## BMI 0.125 0.647
## CRP -0.260 0.523
## IMTmean 0.629
## PWV 0.435 0.389
##
## RC1 RC2
## SS loadings 1.959 1.662
## Proportion Var 0.245 0.208
## Cumulative Var 0.245 0.453Affect Variables
Initial Extraction of Exponents
## Principal Components Analysis
## Call: principal(r = CtrAffectdat, nfactors = 5, rotate = "none", scores = TRUE,
## missing = TRUE, impute = "median")
## Standardized loadings (pattern matrix) based upon correlation matrix
## PC1 PC2 PC3 PC4 PC5 h2 u2 com
## CES 0.87 -0.16 -0.03 -0.41 0.23 1 -1.8e-15 1.7
## acasiPTSD 0.87 -0.19 -0.17 -0.05 -0.41 1 1.0e-15 1.7
## acasiPDSQanx 0.85 -0.11 -0.31 0.35 0.21 1 2.2e-16 1.8
## acasiAnger 0.73 0.68 -0.01 -0.03 -0.03 1 4.4e-16 2.0
## acasiPerStr 0.80 -0.11 0.57 0.15 0.00 1 5.6e-16 1.9
##
## PC1 PC2 PC3 PC4 PC5
## SS loadings 3.40 0.56 0.45 0.32 0.27
## Proportion Var 0.68 0.11 0.09 0.06 0.05
## Cumulative Var 0.68 0.79 0.88 0.95 1.00
## Proportion Explained 0.68 0.11 0.09 0.06 0.05
## Cumulative Proportion 0.68 0.79 0.88 0.95 1.00
##
## Mean item complexity = 1.8
## Test of the hypothesis that 5 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0
## with the empirical chi square 0 with prob < NA
##
## Fit based upon off diagonal values = 1##
## Loadings:
## PC1 PC2 PC3 PC4 PC5
## CES 0.865 -0.164 -0.411 0.235
## acasiPTSD 0.870 -0.195 -0.173 -0.415
## acasiPDSQanx 0.850 -0.112 -0.311 0.354 0.208
## acasiAnger 0.728 0.684
## acasiPerStr 0.801 -0.115 0.567 0.152
##
## PC1 PC2 PC3 PC4 PC5
## SS loadings 3.40 0.559 0.450 0.321 0.271
## Proportion Var 0.68 0.112 0.090 0.064 0.054
## Cumulative Var 0.68 0.792 0.882 0.946 1.000Scree Plot
## [1] 3.4000005 0.5587627 0.4495647 0.3205335 0.2711386
Rotation to Final Solution
##
## Factor analysis with Call: principal(r = CtrAffectdat, nfactors = 1, rotate = "promax",
## scores = TRUE, missing = TRUE, impute = "median")
##
## Test of the hypothesis that 1 factor is sufficient.
## The degrees of freedom for the model is 5 and the objective function was 0.13
## The number of observations was 238 with Chi Square = 29.48 with prob < 1.9e-05
##
## The root mean square of the residuals (RMSA) is 0.08## Principal Components Analysis
## Call: principal(r = CtrAffectdat, nfactors = 1, rotate = "promax",
## scores = TRUE, missing = TRUE, impute = "median")
## Standardized loadings (pattern matrix) based upon correlation matrix
## PC1 h2 u2 com
## CES 0.87 0.75 0.25 1
## acasiPTSD 0.87 0.76 0.24 1
## acasiPDSQanx 0.85 0.72 0.28 1
## acasiAnger 0.73 0.53 0.47 1
## acasiPerStr 0.80 0.64 0.36 1
##
## PC1
## SS loadings 3.40
## Proportion Var 0.68
##
## Mean item complexity = 1
## Test of the hypothesis that 1 component is sufficient.
##
## The root mean square of the residuals (RMSR) is 0.08
## with the empirical chi square 33.83 with prob < 2.6e-06
##
## Fit based upon off diagonal values = 0.98##
## Loadings:
## PC1
## CES 0.865
## acasiPTSD 0.870
## acasiPDSQanx 0.850
## acasiAnger 0.728
## acasiPerStr 0.801
##
## PC1
## SS loadings 3.40
## Proportion Var 0.68Social Support Variables
Initial Extraction of Exponents
## Principal Components Analysis
## Call: principal(r = CtrSocSupdat, nfactors = 3, rotate = "none", scores = TRUE,
## missing = TRUE, impute = "median")
## Standardized loadings (pattern matrix) based upon correlation matrix
## PC1 PC2 PC3 h2 u2 com
## acasiEmoSup 0.86 0.28 0.43 1 0.0e+00 1.7
## acasiInsSup -0.66 0.75 0.01 1 5.6e-16 2.0
## acasiSocInt 0.85 0.30 -0.42 1 -2.2e-16 1.7
##
## PC1 PC2 PC3
## SS loadings 1.91 0.73 0.36
## Proportion Var 0.64 0.24 0.12
## Cumulative Var 0.64 0.88 1.00
## Proportion Explained 0.64 0.24 0.12
## Cumulative Proportion 0.64 0.88 1.00
##
## Mean item complexity = 1.8
## Test of the hypothesis that 3 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0
## with the empirical chi square 0 with prob < NA
##
## Fit based upon off diagonal values = 1Scree Plot
## [1] 1.9093573 0.7277056 0.3629371
Rotation to Final Solution
##
## Factor analysis with Call: principal(r = CtrSocSupdat, nfactors = 1, rotate = "promax",
## scores = TRUE, missing = TRUE, impute = "median")
##
## Test of the hypothesis that 1 factor is sufficient.
## The degrees of freedom for the model is 0 and the objective function was 0.17
## The number of observations was 238 with Chi Square = 40.69 with prob < NA
##
## The root mean square of the residuals (RMSA) is 0.19## Principal Components Analysis
## Call: principal(r = CtrSocSupdat, nfactors = 1, rotate = "promax",
## scores = TRUE, missing = TRUE, impute = "median")
## Standardized loadings (pattern matrix) based upon correlation matrix
## PC1 h2 u2 com
## acasiEmoSup 0.86 0.74 0.26 1
## acasiInsSup -0.66 0.44 0.56 1
## acasiSocInt 0.85 0.73 0.27 1
##
## PC1
## SS loadings 1.91
## Proportion Var 0.64
##
## Mean item complexity = 1
## Test of the hypothesis that 1 component is sufficient.
##
## The root mean square of the residuals (RMSR) is 0.19
## with the empirical chi square 49.26 with prob < NA
##
## Fit based upon off diagonal values = 0.84##
## Loadings:
## PC1
## acasiEmoSup 0.860
## acasiInsSup -0.664
## acasiSocInt 0.854
##
## PC1
## SS loadings 1.909
## Proportion Var 0.636