用国外成熟量表（七个维度）做探索性因子分析，结果出来的是五个维度，剩下的两个维度分别跑到了其他的维度下面（下图黑阴影），但是看起来是很整齐的如下图，解释变量77%，能直接删除这两个维度吗？
| 旋转成份矩阵a |
| | 成份 |
1 | 2 | 3 | 4 | 5 |
| S_SLD1_1 | .172 | .141 | .224 | .734 | .219 |
| S_SLD1_2 | .259 | .215 | .299 | .753 | .203 |
| S_SLD1_3 | .257 | .200 | .259 | .754 | .166 |
| S_SLD1_4 | .157 | .289 | .315 | .672 | .092 |
| S_SLD2_5 | .402 | .603 | .263 | .221 | .189 |
| S_SLD2_6 | .330 | .655 | .225 | .365 | .176 |
| S_SLD2_7 | .087 | .816 | .273 | .134 | .151 |
| S_SLD2_8 | .108 | .787 | .228 | .144 | .154 |
| S_SLD3_9 | .320 | .440 | .207 | .415 | .397 |
| S_SLD3_10 | .357 | .489 | .169 | .383 | .456 |
| S_SLD3_11 | .404 | .448 | .045 | .449 | .376 |
| S_SLD3_12 | .271 | .507 | -.004 | .392 | .366 |
| S_SLD4_13 | .284 | .292 | .150 | .309 | .721 |
| S_SLD4_14 | .384 | .237 | .182 | .160 | .748 |
| S_SLD4_15 | .342 | .250 | .151 | .146 | .782 |
| S_SLD4_16 | .053 | .058 | .420 | .147 | .651 |
| S_SLD5_17 | .225 | .258 | .679 | .279 | .218 |
| S_SLD5_18 | .198 | .192 | .776 | .251 | .154 |
| S_SLD5_19 | .279 | .197 | .698 | .225 | .152 |
| S_SLD5_20 | .169 | .409 | .605 | .186 | .217 |
| S_SLD6_21 | .570 | .235 | .547 | .218 | .132 |
| S_SLD6_22 | .583 | .124 | .518 | .287 | .075 |
| S_SLD6_23 | .569 | .093 | .482 | .208 | .248 |
| S_SLD6_24 | .505 | .161 | .433 | .161 | .341 |
| S_SLD7_25 | .640 | .383 | .250 | .280 | .267 |
| S_SLD7_26 | .765 | .214 | .231 | .218 | .224 |
| S_SLD7_27 | .778 | .181 | .223 | .195 | .233 |
| S_SLD7_28 | .780 | .157 | .109 | .164 | .252 |
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