#s C.4-1
> set12.data <- read.csv("http://mlab.arrow.jp/r_factor/set12.csv") #Ђɂ͏ĂȂ
> head(set12.data)
  no q1 q2 q3 q4 q5 q6 q7 q8 q9 q10 q11 q12
1  1  3  4  3  3  4  4  5  5  5   0   2   1
2  2  4  4  3  4  4  3  4  4  4   3   3   1
3  3  4  5  3  5  5  5  5  5  5   0   0   0
4  4  3  4  1  4  3  5  2  5  2   0   3   0
5  5  4  4  3  4  4  4  4  5  5   0   0   4
6  6  3  4  1  3  3  3  3  5  3   0   2   1
> set10.data <- set12.data[2:11]
> head(set10.data)
  q1 q2 q3 q4 q5 q6 q7 q8 q9 q10
1  3  4  3  3  4  4  5  5  5   0
2  4  4  3  4  4  3  4  4  4   3
3  4  5  3  5  5  5  5  5  5   0
4  3  4  1  4  3  5  2  5  2   0
5  4  4  3  4  4  4  4  5  5   0
6  3  4  1  3  3  3  3  5  3   0
> fa.result <- fa(set10.data, nfactors=3, rotate="varimax")
> print(fa.result, digits=3)
Factor Analysis using method =  minres
Call: fa(r = set10.data, nfactors = 3, rotate = "varimax")
Standardized loadings (pattern matrix) based upon correlation matrix
      MR1    MR3   MR2     h2      u2  com
q1  0.252  0.237 0.936 0.9953 0.00472 1.28
q2  0.213  0.440 0.393 0.3937 0.60633 2.44
q3  0.191  0.200 0.492 0.3190 0.68100 1.65
q4  0.882  0.354 0.199 0.9432 0.05680 1.43
q5  0.508  0.505 0.289 0.5969 0.40307 2.57
q6  0.713  0.473 0.167 0.7595 0.24052 1.87
q7  0.218  0.516 0.136 0.3325 0.66752 1.50
q8  0.052  0.564 0.089 0.3290 0.67099 1.07
q9  0.147  0.443 0.196 0.2563 0.74369 1.63
q10 0.103 -0.003 0.056 0.0138 0.98616 1.55

                        MR1   MR3   MR2
SS loadings           1.772 1.675 1.492
Proportion Var        0.177 0.168 0.149
Cumulative Var        0.177 0.345 0.494
Proportion Explained  0.359 0.339 0.302
Cumulative Proportion 0.359 0.698 1.000

Mean item complexity =  1.7
Test of the hypothesis that 3 factors are sufficient.

The degrees of freedom for the null model are  45  and the objective function was  3.764 with Chi Square of  936.693
The degrees of freedom for the model are 18  and the objective function was  0.086 

The root mean square of the residuals (RMSR) is  0.027 
The df corrected root mean square of the residuals is  0.042 

The harmonic number of observations is  254 with the empirical chi square  16.329  with prob <  0.57 
The total number of observations was  254  with Likelihood Chi Square =  21.32  with prob <  0.264 

Tucker Lewis Index of factoring reliability =  0.9906
RMSEA index =  0.0291  and the 90 % confidence intervals are  0 0.0648
BIC =  -78.352
Fit based upon off diagonal values = 0.995
Measures of factor score adequacy             
                                                    MR1   MR3   MR2
Correlation of (regression) scores with factors   0.932 0.771 0.992
Multiple R square of scores with factors          0.868 0.595 0.983
Minimum correlation of possible factor scores     0.735 0.189 0.966

#s C.4-2
> fa.result <- fa(set12.data[2:13], nfactors=4, rotate="varimax")
> print(fa.result, digits=3)
Factor Analysis using method =  minres
Call: fa(r = set12.data[2:13], nfactors = 4, rotate = "varimax")
Standardized loadings (pattern matrix) based upon correlation matrix
       MR1    MR3    MR4    MR2    h2     u2  com
q1   0.217  0.904  0.219  0.036 0.913 0.0869 1.24
q2   0.240  0.420  0.404 -0.024 0.398 0.6024 2.59
q3   0.173  0.536  0.164 -0.043 0.346 0.6537 1.42
q4   0.903  0.272  0.233  0.013 0.945 0.0554 1.32
q5   0.535  0.335  0.443  0.065 0.598 0.4017 2.69
q6   0.755  0.223  0.376  0.015 0.762 0.2381 1.67
q7   0.294  0.160  0.452 -0.036 0.318 0.6820 2.02
q8   0.117  0.092  0.563 -0.007 0.339 0.6608 1.14
q9   0.174  0.211  0.437  0.066 0.270 0.7301 1.85
q10  0.077  0.059 -0.019  0.916 0.849 0.1506 1.02
q11  0.038 -0.041 -0.040  0.342 0.122 0.8781 1.08
q12 -0.074  0.011  0.080  0.440 0.206 0.7943 1.13

                        MR1   MR3   MR4   MR2
SS loadings           1.950 1.600 1.351 1.165
Proportion Var        0.163 0.133 0.113 0.097
Cumulative Var        0.163 0.296 0.408 0.505
Proportion Explained  0.322 0.264 0.223 0.192
Cumulative Proportion 0.322 0.585 0.808 1.000

Mean item complexity =  1.6
Test of the hypothesis that 4 factors are sufficient.

The degrees of freedom for the null model are  66  and the objective function was  4.111 with Chi Square of  1020.225
The degrees of freedom for the model are 24  and the objective function was  0.126 

The root mean square of the residuals (RMSR) is  0.027 
The df corrected root mean square of the residuals is  0.044 

The harmonic number of observations is  254 with the empirical chi square  23.827  with prob <  0.472 
The total number of observations was  254  with Likelihood Chi Square =  31.028  with prob <  0.153 

Tucker Lewis Index of factoring reliability =  0.9795
RMSEA index =  0.0362  and the 90 % confidence intervals are  0 0.0649
BIC =  -101.868
Fit based upon off diagonal values = 0.993
Measures of factor score adequacy             
                                                    MR1   MR3   MR4   MR2
Correlation of (regression) scores with factors   0.950 0.937 0.747 0.926
Multiple R square of scores with factors          0.903 0.878 0.558 0.857
Minimum correlation of possible factor scores     0.807 0.755 0.115 0.714
