|||
分析过程 | 因子数量 | 解释总变异量 | KMO值 | Bartlett's Test球型检验显著性 | 删除的变量 |
第一次因子分析 | 8 | 63.906% | 0.807 | 0 | VC3、VF2、VF1、VF4、VA4、VG5 |
第二次因子分析 | 6 | 66.787% | 0.782 | 0 | VB2、VG1、VG6 |
第三次因子分析 | 6 | 69.404% | 0.796 | 0 | VD2 |
第四次因子分析 | 6 | 71.300% | 0.805 | 0 |
第一次旋转成份矩阵a | ||||||||
|
成份 | |||||||
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 | |
VB6 |
.740 |
.147 |
-.085 |
.081 |
.051 |
.064 |
.174 |
.122 |
VB1 |
.728 |
.304 |
.217 |
.186 |
.034 |
.257 |
-.174 |
-.084 |
VB3 |
.719 |
.179 |
.319 |
.095 |
.013 |
.178 |
.108 |
.129 |
VB2 |
.698 |
.321 |
.216 |
.020 |
.116 |
.308 |
-.046 |
-.051 |
VB5 |
.697 |
-.024 |
.097 |
.154 |
.013 |
.014 |
.436 |
.056 |
VB4 |
.671 |
.461 |
-.100 |
.154 |
.035 |
.209 |
.010 |
-.056 |
VD1 |
.214 |
.768 |
.112 |
.167 |
-.072 |
.149 |
.020 |
.109 |
VC2 |
.153 |
.766 |
.056 |
.122 |
.221 |
.000 |
.090 |
.093 |
VC1 |
.338 |
.731 |
.044 |
.082 |
.146 |
.087 |
-.048 |
.092 |
VC3 |
.110 |
.473 |
.038 |
-.059 |
.419 |
.135 |
.446 |
.071 |
VF2 |
.235 |
.442 |
.337 |
.361 |
.210 |
.176 |
-.284 |
.152 |
VE4 |
-.014 |
.003 |
.766 |
-.115 |
.229 |
.105 |
.227 |
-.032 |
VE3 |
.244 |
.055 |
.760 |
.138 |
.009 |
.072 |
.159 |
.110 |
VF1 |
.151 |
.259 |
.493 |
.413 |
.161 |
-.099 |
-.056 |
.320 |
VF4 |
.110 |
.368 |
.438 |
.407 |
.108 |
.195 |
.127 |
.092 |
VG4 |
.339 |
.189 |
.137 |
.695 |
.264 |
.140 |
.067 |
.047 |
VG2 |
.031 |
.360 |
-.040 |
.634 |
.109 |
.072 |
.396 |
.087 |
VG6 |
.166 |
-.030 |
.019 |
.596 |
.224 |
.034 |
.152 |
.468 |
VG3 |
.134 |
.047 |
.005 |
.446 |
.727 |
.034 |
.094 |
-.175 |
VF3 |
.136 |
.153 |
.350 |
.028 |
.684 |
.049 |
.041 |
.113 |
VG5 |
-.019 |
.050 |
-.112 |
.202 |
.608 |
.089 |
-.030 |
.581 |
VG1 |
-.105 |
.212 |
.209 |
.155 |
.534 |
.032 |
.279 |
.198 |
VA2 |
.180 |
.017 |
-.019 |
.082 |
.186 |
.822 |
.161 |
.125 |
VA1 |
.360 |
.232 |
.066 |
-.121 |
-.018 |
.667 |
-.125 |
.120 |
VA3 |
.114 |
.314 |
.229 |
.321 |
-.139 |
.663 |
.056 |
-.145 |
VA4 |
.410 |
-.174 |
.178 |
.113 |
.205 |
.483 |
.318 |
.139 |
VE2 |
.072 |
-.057 |
.192 |
.098 |
.063 |
.055 |
.807 |
-.014 |
VE1 |
.269 |
.149 |
.198 |
.220 |
.167 |
.076 |
.632 |
.228 |
VD2 |
.075 |
.274 |
.228 |
.091 |
.019 |
.129 |
.142 |
.785 |
第2次因子分析旋转成份矩阵a | ||||||
|
成份 | |||||
1 |
2 |
3 |
4 |
5 |
6 | |
VB1 |
.773 |
.242 |
-.103 |
.152 |
.291 |
.136 |
VB2 |
.735 |
.261 |
-.062 |
.098 |
.274 |
.223 |
VB4 |
.725 |
.337 |
.050 |
.129 |
.236 |
-.141 |
VB6 |
.715 |
.107 |
.248 |
.082 |
.070 |
-.071 |
VB3 |
.710 |
.212 |
.204 |
.028 |
.153 |
.321 |
VB5 |
.674 |
-.099 |
.515 |
.080 |
.025 |
.093 |
VD1 |
.294 |
.771 |
.047 |
.013 |
.179 |
.033 |
VC2 |
.211 |
.760 |
.042 |
.244 |
-.001 |
.079 |
VC1 |
.394 |
.662 |
-.038 |
.181 |
.165 |
.045 |
VD2 |
-.035 |
.503 |
.465 |
-.029 |
.200 |
.245 |
VE2 |
.084 |
-.149 |
.718 |
.063 |
-.006 |
.218 |
VE1 |
.229 |
.159 |
.683 |
.208 |
.115 |
.231 |
VG2 |
.067 |
.404 |
.510 |
.421 |
.115 |
-.114 |
VG6 |
.077 |
.189 |
.484 |
.462 |
.060 |
-.060 |
VG3 |
.135 |
-.044 |
.076 |
.876 |
.075 |
.054 |
VG4 |
.344 |
.266 |
.265 |
.602 |
.181 |
.031 |
VF3 |
.097 |
.187 |
.005 |
.563 |
.000 |
.468 |
VG1 |
-.126 |
.271 |
.282 |
.480 |
-.015 |
.359 |
VA2 |
.146 |
-.035 |
.204 |
.193 |
.828 |
.055 |
VA1 |
.373 |
.148 |
-.079 |
-.083 |
.697 |
.102 |
VA3 |
.193 |
.266 |
.074 |
.075 |
.695 |
.093 |
VE4 |
.004 |
-.021 |
.117 |
.100 |
.111 |
.840 |
VE3 |
.261 |
.109 |
.232 |
.037 |
.101 |
.697 |
第三次旋转成份矩阵a
|
| ||||||
旋转成份矩阵a |
| ||||||
|
成份 | ||||||
1 |
2 |
3 |
4 |
5 |
6 | ||
VB6 |
.777 |
.142 |
.091 |
.147 |
-.015 |
.080 | |
VB5 |
.720 |
-.049 |
.050 |
.466 |
.121 |
.073 | |
VB1 |
.704 |
.300 |
.310 |
-.149 |
.182 |
.206 | |
VB3 |
.692 |
.246 |
.173 |
.139 |
.349 |
.018 | |
VB4 |
.689 |
.383 |
.277 |
.025 |
-.143 |
.118 | |
VD1 |
.210 |
.800 |
.186 |
.051 |
.034 |
.004 | |
VC2 |
.147 |
.782 |
.009 |
.055 |
.059 |
.213 | |
VC1 |
.355 |
.689 |
.175 |
-.073 |
.064 |
.187 | |
VD2 |
.006 |
.497 |
.161 |
.341 |
.353 |
-.099 | |
VA2 |
.141 |
-.014 |
.837 |
.212 |
.050 |
.161 | |
VA1 |
.356 |
.154 |
.707 |
-.133 |
.133 |
-.077 | |
VA3 |
.107 |
.310 |
.699 |
.089 |
.115 |
.096 | |
VE2 |
.090 |
-.104 |
.009 |
.775 |
.197 |
.060 | |
VE1 |
.190 |
.226 |
.115 |
.731 |
.237 |
.210 | |
VG2 |
.095 |
.436 |
.113 |
.537 |
-.144 |
.335 | |
VE4 |
-.023 |
-.031 |
.119 |
.147 |
.790 |
.109 | |
VE3 |
.253 |
.122 |
.088 |
.158 |
.756 |
.055 | |
VG3 |
.092 |
.019 |
.082 |
.162 |
.019 |
.898 | |
VF3 |
.026 |
.225 |
-.005 |
.025 |
.477 |
.594 | |
VG4 |
.324 |
.329 |
.173 |
.229 |
.095 |
.585 | |
第4次因子分析
旋转成份矩阵a | ||||||
|
成份 | |||||
1 |
2 |
3 |
4 |
5 |
6 | |
VB6 |
.787 |
.140 |
.089 |
.133 |
.098 |
-.031 |
VB5 |
.723 |
-.042 |
.051 |
.461 |
.071 |
.121 |
VB3 |
.692 |
.249 |
.170 |
.133 |
.031 |
.349 |
VB1 |
.686 |
.336 |
.307 |
-.133 |
.199 |
.181 |
VB4 |
.668 |
.422 |
.274 |
.046 |
.087 |
-.132 |
VD1 |
.188 |
.814 |
.177 |
.073 |
-.022 |
.063 |
VC2 |
.119 |
.804 |
.002 |
.087 |
.183 |
.086 |
VC1 |
.344 |
.696 |
.166 |
-.063 |
.189 |
.068 |
VA2 |
.162 |
-.033 |
.836 |
.191 |
.190 |
.027 |
VA1 |
.373 |
.140 |
.703 |
-.160 |
-.035 |
.120 |
VA3 |
.059 |
.377 |
.699 |
.142 |
.022 |
.160 |
VE2 |
.090 |
-.109 |
.012 |
.778 |
.041 |
.218 |
VE1 |
.200 |
.202 |
.113 |
.724 |
.214 |
.240 |
VG2 |
.067 |
.465 |
.112 |
.581 |
.270 |
-.123 |
VG3 |
.085 |
.039 |
.084 |
.190 |
.889 |
-.023 |
VF3 |
.047 |
.189 |
-.009 |
.007 |
.658 |
.434 |
VG4 |
.318 |
.337 |
.171 |
.247 |
.576 |
.067 |
VE4 |
-.044 |
-.010 |
.122 |
.166 |
.099 |
.815 |
VE3 |
.247 |
.121 |
.087 |
.161 |
.066 |
.764 |
终于没有可以删除的变量了。
看了别人的一些文章,发现还有可以删除的变量。
比如因子6,因为只有2个变量,我们可以说实际可代表性,比较差。
所以又可以删除因子6了。
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