Thurstone & Thrustone(1941) 21変数　基本精神能力テスト
variables
1:Identical Numbers(p) 2:Face(P) 3:Mirror Reading(P) 4:First Names(M) 5:Figure recognition(M) 6:Word-Number(M) 7:Sentences(V) 8:Vocabulary(V) 9:Completion(V) 10:First-Letters(W)
11:Four-Letter Words(W) 12:Suffixes(W) 13:Flags(S) 14:Figures(S) 15:Cards(S) 16:Addition(N) 17:Multiplication(N) 18:Three-Highter(N) 19:Letter Series（R） 20:Pedigrees（R）
          Factor analysis for continuous variables
               programmed by Tamaki Hattori
                     < 12/03/2002 >
 
 
 The following lines were read from file C:\My Documents\hattori.cmd                                                     
> FILE = hattori.dat                                                                                                    
> NSUBJECTS =  437                                                                                                      
> NITEMS =     21                                                                                                       
> DATA TYPE = COR                                                                                                       
> NFACTORS = 1-10                                                                                                       
> PARALLEL = 100                                                                                                        
 
 
 Correlation matrix
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
1 1:Identical Numbers(p) 1:Identical Numbers(p)
2 2:Face(P)  0.461 2:Face(P)
3 3:Mirror Reading(P)  0.430  0.505 3:Mirror Reading(P)
4 4:First Names(M)  0.129  0.209  0.263 4:First Names(M)
5 5:Figure recognition(M)  0.156  0.338  0.224  0.280 5:Figure recognition(M)
6 6:Word-Number(M)  0.129  0.175  0.209  0.478  0.292 6:Word-Number(M)
7 7:Sentences(V)  0.261  0.297  0.343  0.295  0.151  0.234 7:Sentences(V)
8 8:Vocabulary(V)  0.247  0.264  0.349  0.364  0.242  0.260  0.829 8:Vocabulary(V)
9 9:Completion(V)  0.204  0.400  0.332  0.282  0.234  0.251  0.768  0.775 9:Completion(V)
10 10:First-Letters(W)  0.297  0.256  0.447  0.286  0.243  0.240  0.419  0.472  0.428 10:First-Letters(W)
11 11:Four-Letter Words(W)  0.239  0.221  0.372  0.299  0.184  0.217  0.356  0.415  0.354  0.654 11:Four-Letter Words(W)
12 12:Suffixes(W)  0.231  0.183  0.350  0.311  0.122  0.236  0.407  0.482  0.433  0.557  0.514 12:Suffixes(W)
13 13:Flags(S)  0.181  0.416  0.279  0.103  0.227  0.100  0.108  0.115  0.272  0.176  0.192  0.100 13:Flags(S)
14 14:Figures(S)  0.143  0.402  0.291  0.046  0.183  0.078  0.033  0.061  0.205  0.092  0.165  0.009  0.636 14:Figures(S)
15 15:Cards(S)  0.221  0.424  0.298  0.061  0.252  0.166  0.108  0.125  0.238  0.127  0.144  0.066  0.626  0.709 15:Cards(S)
16 16:Addition(N)  0.434  0.339  0.317  0.196  0.121  0.216  0.298  0.323  0.296  0.293  0.261  0.233  0.249  0.138  0.190 16:Addition(N)
17 17:Multiplication(N)  0.497  0.334  0.354  0.268  0.040  0.203  0.309  0.347  0.271  0.348  0.308  0.254  0.183  0.091  0.103  0.654 17:Multiplication(N)
18 18:Three-Highter(N)  0.369  0.433  0.347  0.261  0.155  0.140  0.351  0.369  0.385  0.319  0.334  0.293  0.369  0.254  0.291  0.527  0.541 18:Three-Highter(N)
19 19:Letter Series（R）  0.292  0.378  0.418  0.320  0.290  0.249  0.492  0.468  0.446  0.391  0.367  0.305  0.271  0.180  0.225  0.399  0.407  0.471 19:Letter Series（R）
20 20:Pedigrees（R）  0.259  0.398  0.385  0.381  0.254  0.254  0.555  0.525  0.523  0.355  0.323  0.319  0.185  0.147  0.179  0.262  0.296  0.437  0.613 20:Pedigrees（R）
21 21:Letter Grouping（R）  0.348  0.401  0.460  0.285  0.217  0.192  0.425  0.381  0.396  0.398  0.381  0.303  0.279  0.191  0.245  0.356  0.394  0.429  0.610  0.496 21:Letter Grouping（R）
1:Identical Numbers(p) 2:Face(P) 3:Mirror Reading(P) 4:First Names(M) 5:Figure recognition(M) 6:Word-Number(M) 7:Sentences(V) 8:Vocabulary(V) 9:Completion(V) 10:First-Letters(W) 11:Four-Letter Words(W) 12:Suffixes(W) 13:Flags(S) 14:Figures(S) 15:Cards(S) 16:Addition(N) 17:Multiplication(N) 18:Three-Highter(N) 19:Letter Series（R） 20:Pedigrees（R） 21:Letter Grouping（R）
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
 
 Statistics for determining the number of factors
 Chi^2 of independent model =  4716.8158
# of FACTORS MAP-TEST[1] RAW-EIGEN[2] PA-EIG-M[3] PA-EIG95[4] SMC-EIGEN PA-SMC-M[5] PA-SMC-95[6] SE-SCREE[7]
3 5 4 3 9 7 7 7
1  0.03297  7.3665  1.4120  1.4988  6.9132  0.4650  0.5599  1.2460
2  0.02787  2.3778  1.3395  1.3861  1.9592  0.3901  0.4469  0.2878
3  0.02536  1.5709  1.2842  1.3307  1.1107  0.3339  0.3910  0.1599
4  0.02585  1.2565  1.2361  1.2705  0.7725  0.2834  0.3269  0.1223
5  0.02657  1.1824  1.1975  1.2311  0.6209  0.2433  0.2786  0.1064
6  0.02830  0.9406  1.1569  1.1866  0.4271  0.2023  0.2372  0.0730
7  0.02992  0.8520  1.1211  1.1473  0.3382  0.1643  0.1921  0.0588
8  0.03661  0.7108  1.0858  1.1139  0.0916  0.1286  0.1548  0.0367
9[8]  0.04508  0.5931  1.0522  1.0740  0.0772  0.0950  0.1205  0.0222
10  0.05643  0.4947  1.0187  1.0467 - 0.0081  0.0611  0.0897  0.0193
# of FACTORS CHI^2 DF AIC1[9] AIC2[10] BIC1[11] BIC2[12] CAIC1[13] CAIC2[14]
8 8 7 7 5 5
1  2074.01 189  2158.01  1696.01  2329.37  924.90  2371.37  735.90
2  1315.99 169  1439.99  977.99  1692.94  288.48  1754.94  119.48
3  807.29 150  969.29  507.29  1299.76 - 104.70  1380.76 - 254.70
4  540.48 132  738.48  276.48  1142.39 - 262.07  1241.39 - 394.07
5  357.22 115  589.22  127.22  1062.49 - 341.98  1178.49 - 456.98
6  246.47 99  510.47  48.47  1049.02 - 355.45  1181.02 - 454.45
7  151.47 84  445.47 - 16.53  1045.22 - 359.24  1192.22 - 443.24
8  104.11 70  426.11 - 35.89  1082.98 - 321.49  1243.98 - 391.49
9[15]  868.40 57  1216.40  754.40  1926.31  521.85  2100.31  464.85
10 NaN 45 NaN NaN NaN NaN NaN NaN
p=  0.0000
# of FACTORS RMSEA[16] GFI[17] AGFI[18] PGFI[19] EGFI[20] RGFI[21] RMSR[22]
7 5 8 3 5 3
1  0.1512  0.6326  0.5510  0.5176  0.9604  0.6587  0.1111
2  0.1248  0.7052  0.5970  0.5159  0.9645  0.7311  0.0783
3  0.1003  0.8162  0.7169  0.5300  0.9683  0.8429  0.0577
4  0.0842  0.8698  0.7721  0.4970  0.9720  0.8948  0.0446
5  0.0695  0.9117  0.8226  0.4539  0.9756  0.9345  0.0353
6  0.0585  0.9381  0.8556  0.4020  0.9789  0.9583  0.0242
7  0.0429  0.9590  0.8873  0.3487  0.9820  0.9766  0.0158
8  0.0334  0.9712  0.9049  0.2943  0.9850  0.9860  0.0128
9[23]  0.1807  0.8071  0.2183  0.1992  0.9877  0.8171  0.0328
10  0.0000 NaN NaN NaN  0.9903 NaN NaN
# of FACTORS NFI[24] NNFI[25] CFI[26]
5 7 6
1  0.5603  0.5353  0.5817
2  0.7210  0.6838  0.7455
3  0.8288  0.7958  0.8542
4  0.8854  0.8558  0.9094
5  0.9243  0.9019  0.9463
6  0.9477  0.9306  0.9673
7  0.9679  0.9626  0.9850
8  0.9779  0.9773  0.9924
9[27]  0.8159  0.3367  0.8200
10 NaN NaN -NaN
[1]
Minimum Average Partial (MAP) test (Velicer,1976)
[2]
principle component anlaysis:Kaiser 基準：固有値 1.0 以上
[3]
Parallel Analysis: Mean　(Horn, 1965)
[4]
Parallel Analysis: 95%
[5]
Parallel Analysis:SMC Mean
[6]
Parallel Analysis:SMC 95%
[7]
Stancard Error Scree　(Zoski, K. W., and Jurs, S. ,1996)
[8]
不適解：収束せず
[9]
Akaike information criterion (Akaike, 1973,1987):: chi2 - 2 * パラメータ数 ->Amos
[10]
Akaike information criterion (Akaike, 1973,1987): chi2 - 2 * df　->EQS, CALIS
[11]
Bayes information criterion (Schwarz,1978; Raftery, 1993):chi2 - Log(N) * パラメータ数
[12]
Bayes information criterion (Schwarz,1978; Raftery, 1993):chi2 - Log(N) * df
[13]
Consistent AIC (Bozdogan, 1987): Chi2-(1+Log(N))*パラメータ数
[14]
Consistent AIC (Bozdogan, 1987): Chi2-(1+Log(N))*df
[15]
不適解：収束せず
[16]
Root Mean Square Error of Approximation (Steiger and Lind, 1980).母集団
[17]
Goodness of Fit: LISREL
[18]
Adjusted Goodness of Fit:自由度調整済みGFI
[19]
Parsinomy Goodness of Fit: Mulaik et al.(1989) 節約基準
[20]
GFI, AFI 修正のための項: GFIの近似期待値　Maiti and Mukherjee(1990) MBR
Sharma(1996) book
[21]
Relative Goodness of Fit　：GFI/EGFI
[22]
Root Mean Square Residual
モデル間の相対比較用
[23]
不適解：収束せず
[24]
Bentler-Browne normed fit index: 独立モデルとモデルの比較
[25]
Bentler-Browne non-normed fit index: Tucker-Lewis Index (TLI)のこと
[26]
Comparative Fit Index: Bentler(1990) RNI と同じ
[27]
不適解：収束せず