#s C.1-1
> f3L <- fa(five.data, nfactors=3, rotate="none")$loadings
> f3L

Loadings:
     MR1    MR2    MR3   
  0.706  0.562       
Љ  0.436  0.183 -0.101
p  0.433  0.212  0.277
w  0.786 -0.526       
  0.639 -0.243       

                 MR1   MR2   MR3
SS loadings    1.903 0.730 0.095
Proportion Var 0.381 0.146 0.019
Cumulative Var 0.381 0.527 0.546

#s C.1-2
> cfT(f3L, kappa=1/(2*5))
Orthogonal rotation method Crawford-Ferguson:k=0.1 converged.
Loadings:
       MR1   MR2     MR3
 0.167 0.891  0.0134
Љ 0.211 0.432 -0.0536
p 0.188 0.411  0.3240
w 0.939 0.115  0.0164
 0.643 0.235 -0.0011

Rotating matrix:
         [,1]   [,2]   [,3]
[1,]  0.75681  0.650 0.0728
[2,] -0.65363  0.753 0.0795
[3,] -0.00313 -0.108 0.9942

#sC.1-3
> cfT(f3L, kappa=3/(2*5))
Orthogonal rotation method Crawford-Ferguson:k=0.3 converged.
Loadings:
       MR1   MR2     MR3
 0.151 0.885 0.12244
Љ 0.205 0.438 0.00603
p 0.166 0.373 0.37725
w 0.935 0.124 0.07455
 0.638 0.241 0.05657

Rotating matrix:
        [,1]   [,2]  [,3]
[1,]  0.7413  0.646 0.182
[2,] -0.6695  0.731 0.133
[3,] -0.0475 -0.221 0.974

#s C.1-4
> cfT(f3L, kappa=1)
Orthogonal rotation method Crawford-Ferguson:k=1 converged.
Loadings:
        MR1    MR2   MR3
 0.0402 0.7993 0.426
Љ 0.1599 0.4121 0.197
p 0.0289 0.2328 0.504
w 0.8684 0.0871 0.365
 0.5784 0.2065 0.302

Rotating matrix:
       [,1]   [,2]  [,3]
[1,]  0.611  0.549 0.570
[2,] -0.738  0.655 0.160
[3,] -0.285 -0.519 0.806

#s C.1-5
> fa.result <- fa(five.data, nfactors=3, rotate="oblimin", gam=0.5)
> print(fa.result, digits=3)
Factor Analysis using method =  minres
Call: fa(r = five.data, nfactors = 3, rotate = "oblimin", gam = 0.5)
Standardized loadings (pattern matrix) based upon correlation matrix
        MR1    MR2    MR3    h2    u2  com
 -0.160  1.061  0.123 0.822 0.178 1.07
Љ  0.062  0.441 -0.004 0.234 0.766 1.04
p  0.155  0.613  0.482 0.309 0.691 2.04
w  1.100 -0.167  0.137 0.895 0.105 1.08
  0.685  0.075  0.093 0.469 0.531 1.06

                        MR1   MR2    MR3
SS loadings           1.476 1.372 -0.119
Proportion Var        0.295 0.274 -0.024
Cumulative Var        0.295 0.569  0.546
Proportion Explained  0.541 0.503 -0.044
Cumulative Proportion 0.541 1.044  1.000

 With factor correlations of 
       MR1    MR2    MR3
MR1  1.000  0.614 -0.547
MR2  0.614  1.000 -0.606
MR3 -0.547 -0.606  1.000

Mean item complexity =  1.3
Test of the hypothesis that 3 factors are sufficient.

The degrees of freedom for the null model are  10  and the objective function was  1.036 with Chi Square of  268.836
The degrees of freedom for the model are -2  and the objective function was  0 

The root mean square of the residuals (RMSR) is  0 
The df corrected root mean square of the residuals is  NA 

The harmonic number of observations is  263 with the empirical chi square  0  with prob <  NA 
The total number of observations was  263  with Likelihood Chi Square =  0  with prob <  NA 

Tucker Lewis Index of factoring reliability =  1.0389
Fit based upon off diagonal values = 1
Measures of factor score adequacy             
                                                    MR1   MR2    MR3
Correlation of (regression) scores with factors   0.948 0.918  0.578
Multiple R square of scores with factors          0.898 0.842  0.334
Minimum correlation of possible factor scores     0.796 0.684 -0.332

#s C.1-6
> f3L <- fa(five.data, nfactors=3, rotate="none")loadings
> ob.result <- oblimin(f3L, gam=0.5) 
> print(ob.result, digits=3)
Oblique rotation method Oblimin Biquartimin converged.
Loadings:
        MR1     MR2      MR3
 -0.160  1.0613  0.12283
Љ  0.062  0.4408 -0.00406
p  0.155  0.6127  0.48214
w  1.100 -0.1667  0.13718
  0.685  0.0746  0.09317

Rotating matrix:
       [,1] [,2]  [,3]
[1,]  0.675 0.59 0.242
[2,] -1.083 1.20 0.104
[3,]  0.335 0.37 1.281

Phi:
       [,1]   [,2]   [,3]
[1,]  1.000  0.614 -0.547
[2,]  0.614  1.000 -0.606
[3,] -0.547 -0.606  1.000

#s C.1-7
> fa(five.data, nfactors=3, rotate="varimax")
Factor Analysis using method =  minres
Call: fa(r = five.data, nfactors = 3, rotate = "varimax")
Standardized loadings (pattern matrix) based upon correlation matrix
      MR1  MR2  MR3   h2   u2 com
 0.12 0.83 0.34 0.82 0.18 1.4
Љ 0.19 0.43 0.12 0.23 0.77 1.6
p 0.14 0.27 0.46 0.31 0.69 1.8
w 0.93 0.12 0.14 0.89 0.11 1.1
 0.63 0.24 0.14 0.47 0.53 1.4

                       MR1  MR2  MR3
SS loadings           1.32 1.02 0.38
Proportion Var        0.26 0.20 0.08
Cumulative Var        0.26 0.47 0.55
Proportion Explained  0.49 0.37 0.14
Cumulative Proportion 0.49 0.86 1.00

Mean item complexity =  1.4
Test of the hypothesis that 3 factors are sufficient.

The degrees of freedom for the null model are  10  and the objective function was  1.04 with Chi Square of  268.84
The degrees of freedom for the model are -2  and the objective function was  0 

The root mean square of the residuals (RMSR) is  0 
The df corrected root mean square of the residuals is  NA 

The harmonic number of observations is  263 with the empirical chi square  0  with prob <  NA 
The total number of observations was  263  with Likelihood Chi Square =  0  with prob <  NA 

Tucker Lewis Index of factoring reliability =  1.039
Fit based upon off diagonal values = 1
Measures of factor score adequacy             
                                                   MR1  MR2   MR3
Correlation of (regression) scores with factors   0.94 0.85  0.50
Multiple R square of scores with factors          0.88 0.71  0.25
Minimum correlation of possible factor scores     0.77 0.43 -0.51
> fa(five.data, nfactors=3, rotate="Varimax")
Factor Analysis using method =  minres
Call: fa(r = five.data, nfactors = 3, rotate = "Varimax")
Standardized loadings (pattern matrix) based upon correlation matrix
      MR1  MR2   MR3   h2   u2 com
 0.16 0.89  0.05 0.82 0.18 1.1
Љ 0.21 0.44 -0.03 0.23 0.77 1.4
p 0.18 0.40  0.34 0.31 0.69 2.4
w 0.94 0.12  0.03 0.89 0.11 1.0
 0.64 0.24  0.02 0.47 0.53 1.3

                       MR1  MR2  MR3
SS loadings           1.39 1.21 0.12
Proportion Var        0.28 0.24 0.02
Cumulative Var        0.28 0.52 0.55
Proportion Explained  0.51 0.45 0.04
Cumulative Proportion 0.51 0.96 1.00

Mean item complexity =  1.4
Test of the hypothesis that 3 factors are sufficient.

The degrees of freedom for the null model are  10  and the objective function was  1.04 with Chi Square of  268.84
The degrees of freedom for the model are -2  and the objective function was  0 

The root mean square of the residuals (RMSR) is  0 
The df corrected root mean square of the residuals is  NA 

The harmonic number of observations is  263 with the empirical chi square  0  with prob <  NA 
The total number of observations was  263  with Likelihood Chi Square =  0  with prob <  NA 

Tucker Lewis Index of factoring reliability =  1.039
Fit based upon off diagonal values = 1
Measures of factor score adequacy             
                                                   MR1  MR2   MR3
Correlation of (regression) scores with factors   0.95 0.90  0.36
Multiple R square of scores with factors          0.89 0.82  0.13
Minimum correlation of possible factor scores     0.79 0.64 -0.74

#s C.1-8
> fa(five.data, nfactors=3, rotate="promax", pro.m=4)
Factor Analysis using method =  minres
Call: fa(r = five.data, nfactors = 3, rotate = "promax", pro.m = 4)
Standardized loadings (pattern matrix) based upon correlation matrix
       MR1   MR2   MR3   h2   u2 com
 -0.14  0.89  0.11 0.82 0.18 1.1
Љ  0.08  0.46 -0.04 0.23 0.77 1.1
p  0.02  0.06  0.50 0.31 0.69 1.0
w  0.99 -0.12  0.02 0.89 0.11 1.0
  0.62  0.10  0.01 0.47 0.53 1.0

                       MR1  MR2  MR3
SS loadings           1.34 1.04 0.35
Proportion Var        0.27 0.21 0.07
Cumulative Var        0.27 0.48 0.55
Proportion Explained  0.49 0.38 0.13
Cumulative Proportion 0.49 0.87 1.00

 With factor correlations of 
     MR1  MR2  MR3
MR1 1.00 0.50 0.44
MR2 0.50 1.00 0.71
MR3 0.44 0.71 1.00

Mean item complexity =  1.1
Test of the hypothesis that 3 factors are sufficient.

The degrees of freedom for the null model are  10  and the objective function was  1.04 with Chi Square of  268.84
The degrees of freedom for the model are -2  and the objective function was  0 

The root mean square of the residuals (RMSR) is  0 
The df corrected root mean square of the residuals is  NA 

The harmonic number of observations is  263 with the empirical chi square  0  with prob <  NA 
The total number of observations was  263  with Likelihood Chi Square =  0  with prob <  NA 

Tucker Lewis Index of factoring reliability =  1.039
Fit based upon off diagonal values = 1
Measures of factor score adequacy             
                                                   MR1  MR2  MR3
Correlation of (regression) scores with factors   0.95 0.92 0.76
Multiple R square of scores with factors          0.91 0.84 0.58
Minimum correlation of possible factor scores     0.82 0.69 0.17
> fa(five.data, nfactors=3, rotate="promax", pro.m=2)
Factor Analysis using method =  minres
Call: fa(r = five.data, nfactors = 3, rotate = "promax", pro.m = 2)
Standardized loadings (pattern matrix) based upon correlation matrix
       MR1   MR2  MR3   h2   u2 com
 -0.05  0.82 0.18 0.82 0.18 1.1
Љ  0.12  0.42 0.02 0.23 0.77 1.2
p  0.05  0.15 0.45 0.31 0.69 1.2
w  0.95 -0.04 0.03 0.89 0.11 1.0
  0.61  0.13 0.04 0.47 0.53 1.1

                       MR1  MR2  MR3
SS loadings           1.33 1.03 0.37
Proportion Var        0.27 0.21 0.07
Cumulative Var        0.27 0.47 0.55
Proportion Explained  0.49 0.38 0.14
Cumulative Proportion 0.49 0.86 1.00

 With factor correlations of 
     MR1  MR2  MR3
MR1 1.00 0.35 0.31
MR2 0.35 1.00 0.49
MR3 0.31 0.49 1.00

Mean item complexity =  1.1
Test of the hypothesis that 3 factors are sufficient.

The degrees of freedom for the null model are  10  and the objective function was  1.04 with Chi Square of  268.84
The degrees of freedom for the model are -2  and the objective function was  0 

The root mean square of the residuals (RMSR) is  0 
The df corrected root mean square of the residuals is  NA 

The harmonic number of observations is  263 with the empirical chi square  0  with prob <  NA 
The total number of observations was  263  with Likelihood Chi Square =  0  with prob <  NA 

Tucker Lewis Index of factoring reliability =  1.039
Fit based upon off diagonal values = 1
Measures of factor score adequacy             
                                                   MR1  MR2   MR3
Correlation of (regression) scores with factors   0.95 0.90  0.67
Multiple R square of scores with factors          0.90 0.81  0.45
Minimum correlation of possible factor scores     0.81 0.63 -0.10
