Parallel Analysis: Iteration 0
Parallel Analysis: Iteration 1
Parallel Analysis: Iteration 2
Parallel Analysis: Iteration 3
Parallel Analysis: Iteration 4
Parallel Analysis: Iteration 5
Parallel Analysis: Iteration 6
Parallel Analysis: Iteration 7
Parallel Analysis: Iteration 8
Parallel Analysis: Iteration 9
Parallel Analysis: Iteration 10
Parallel Analysis: Iteration 11
Parallel Analysis: Iteration 12
Parallel Analysis: Iteration 13
Parallel Analysis: Iteration 14
Parallel Analysis: Iteration 15
Parallel Analysis: Iteration 16
Parallel Analysis: Iteration 17
Parallel Analysis: Iteration 18
Parallel Analysis: Iteration 19
Parallel Analysis: Iteration 20
Parallel Analysis: Iteration 21
Parallel Analysis: Iteration 22
Parallel Analysis: Iteration 23
Parallel Analysis: Iteration 24
Parallel Analysis: Iteration 25
Parallel Analysis: Iteration 26
Parallel Analysis: Iteration 27
Parallel Analysis: Iteration 28
Parallel Analysis: Iteration 29
Parallel Analysis: Iteration 30
Parallel Analysis: Iteration 31
Parallel Analysis: Iteration 32
Parallel Analysis: Iteration 33
Parallel Analysis: Iteration 34
Parallel Analysis: Iteration 35
Parallel Analysis: Iteration 36
Parallel Analysis: Iteration 37
Parallel Analysis: Iteration 38
Parallel Analysis: Iteration 39
Parallel Analysis: Iteration 40
Parallel Analysis: Iteration 41
Parallel Analysis: Iteration 42
Parallel Analysis: Iteration 43
Parallel Analysis: Iteration 44
Parallel Analysis: Iteration 45
Parallel Analysis: Iteration 46
Parallel Analysis: Iteration 47
Parallel Analysis: Iteration 48
Parallel Analysis: Iteration 49
Analysis 2016-03-26 02:42:37 +0000
= Statsample::Factor::ParallelAnalysis
There are 3 real factors on data
== Principal Component Analysis
Number of factors: 8
Communalities
+----------+---------+------------+--------+
| Variable | Initial | Extraction | % |
+----------+---------+------------+--------+
| v0 | 1.000 | 0.718 | 71.814 |
| v1 | 1.000 | 0.806 | 80.592 |
| v10 | 1.000 | 0.742 | 74.220 |
| v11 | 1.000 | 0.672 | 67.184 |
| v12 | 1.000 | 0.767 | 76.672 |
| v13 | 1.000 | 0.525 | 52.483 |
| v14 | 1.000 | 0.613 | 61.319 |
| v15 | 1.000 | 0.767 | 76.689 |
| v16 | 1.000 | 0.580 | 58.006 |
| v17 | 1.000 | 0.614 | 61.435 |
| v18 | 1.000 | 0.571 | 57.060 |
| v19 | 1.000 | 0.606 | 60.624 |
| v2 | 1.000 | 0.745 | 74.486 |
| v20 | 1.000 | 0.735 | 73.461 |
| v21 | 1.000 | 0.835 | 83.501 |
| v22 | 1.000 | 0.874 | 87.361 |
| v23 | 1.000 | 0.830 | 82.958 |
| v24 | 1.000 | 0.900 | 90.029 |
| v25 | 1.000 | 0.930 | 93.029 |
| v26 | 1.000 | 0.940 | 94.045 |
| v27 | 1.000 | 0.957 | 95.748 |
| v28 | 1.000 | 0.975 | 97.489 |
| v29 | 1.000 | 0.979 | 97.931 |
| v3 | 1.000 | 0.675 | 67.468 |
| v4 | 1.000 | 0.676 | 67.614 |
| v5 | 1.000 | 0.639 | 63.899 |
| v6 | 1.000 | 0.707 | 70.699 |
| v7 | 1.000 | 0.702 | 70.152 |
| v8 | 1.000 | 0.593 | 59.331 |
| v9 | 1.000 | 0.774 | 77.365 |
+----------+---------+------------+--------+
Total Variance Explained
+--------------+---------+---------+---------+
| Component | E.Total | % | Cum. % |
+--------------+---------+---------+---------+
| Component 1 | 11.635 | 38.784% | 38.784 |
| Component 2 | 2.228 | 7.425% | 46.209 |
| Component 3 | 1.868 | 6.225% | 52.434 |
| Component 4 | 1.781 | 5.936% | 58.371 |
| Component 5 | 1.503 | 5.009% | 63.380 |
| Component 6 | 1.275 | 4.250% | 67.630 |
| Component 7 | 1.149 | 3.830% | 71.460 |
| Component 8 | 1.009 | 3.362% | 74.822 |
| Component 9 | 0.948 | 3.162% | 77.984 |
| Component 10 | 0.813 | 2.709% | 80.692 |
| Component 11 | 0.776 | 2.585% | 83.278 |
| Component 12 | 0.688 | 2.292% | 85.570 |
| Component 13 | 0.584 | 1.945% | 87.515 |
| Component 14 | 0.516 | 1.719% | 89.235 |
| Component 15 | 0.490 | 1.633% | 90.868 |
| Component 16 | 0.454 | 1.512% | 92.380 |
| Component 17 | 0.416 | 1.388% | 93.768 |
| Component 18 | 0.345 | 1.149% | 94.916 |
| Component 19 | 0.322 | 1.073% | 95.990 |
| Component 20 | 0.276 | 0.919% | 96.908 |
| Component 21 | 0.240 | 0.800% | 97.708 |
| Component 22 | 0.206 | 0.685% | 98.394 |
| Component 23 | 0.132 | 0.439% | 98.832 |
| Component 24 | 0.098 | 0.327% | 99.159 |
| Component 25 | 0.095 | 0.315% | 99.475 |
| Component 26 | 0.064 | 0.215% | 99.690 |
| Component 27 | 0.050 | 0.167% | 99.857 |
| Component 28 | 0.030 | 0.100% | 99.957 |
| Component 29 | 0.010 | 0.034% | 99.990 |
| Component 30 | 0.003 | 0.010% | 100.000 |
+--------------+---------+---------+---------+
Component matrix
+-----+-------+-------+-------+-------+-------+-------+-------+-------+
| | PC_1 | PC_2 | PC_3 | PC_4 | PC_5 | PC_6 | PC_7 | PC_8 |
+-----+-------+-------+-------+-------+-------+-------+-------+-------+
| v0 | .029 | .599 | .211 | -.365 | -.017 | -.128 | -.379 | .145 |
| v1 | -.011 | .431 | .139 | .104 | -.148 | .729 | -.163 | -.096 |
| v10 | -.309 | .211 | -.302 | -.367 | -.453 | .220 | .102 | .335 |
| v11 | -.386 | .373 | .258 | .394 | -.326 | -.091 | -.001 | .217 |
| v12 | -.351 | .063 | .544 | -.128 | .016 | .019 | .567 | -.070 |
| v13 | -.450 | .432 | .243 | .120 | .114 | -.130 | -.172 | -.046 |
| v14 | -.539 | -.069 | .166 | .273 | .024 | .395 | .018 | .242 |
| v15 | -.576 | -.032 | -.210 | .192 | -.494 | .202 | .215 | -.147 |
| v16 | -.546 | -.378 | .264 | -.110 | .074 | -.006 | .060 | .218 |
| v17 | -.627 | .258 | .005 | .151 | .093 | .131 | -.271 | -.181 |
| v18 | -.716 | -.171 | -.084 | .120 | .020 | .049 | -.050 | .045 |
| v19 | -.718 | .088 | -.063 | .054 | -.249 | .111 | .007 | .047 |
| v2 | -.064 | -.591 | .400 | .197 | -.086 | .126 | -.361 | -.199 |
| v20 | -.826 | -.133 | .017 | .069 | .132 | .099 | -.008 | -.053 |
| v21 | -.882 | -.147 | .001 | -.034 | .014 | .091 | -.141 | -.081 |
| v22 | -.904 | .033 | -.012 | -.147 | .040 | -.149 | -.059 | .078 |
| v23 | -.890 | .023 | .109 | -.112 | .085 | -.012 | .041 | -.056 |
| v24 | -.924 | .125 | -.011 | -.025 | .097 | -.089 | .101 | .054 |
| v25 | -.937 | .054 | -.084 | -.060 | .083 | -.176 | -.006 | -.025 |
| v26 | -.961 | -.054 | -.052 | -.028 | .076 | -.061 | .006 | -.022 |
| v27 | -.965 | -.016 | -.070 | .006 | .122 | -.048 | .016 | -.058 |
| v28 | -.970 | .015 | -.106 | -.009 | .126 | -.070 | .029 | -.012 |
| v29 | -.974 | -.007 | -.108 | .002 | .117 | -.057 | .004 | -.035 |
| v3 | -.036 | .422 | .209 | -.062 | -.345 | -.231 | .368 | -.374 |
| v4 | -.107 | -.546 | .428 | -.164 | -.320 | .069 | .046 | -.217 |
| v5 | .010 | .055 | .656 | .203 | .004 | -.067 | .015 | .400 |
| v6 | .078 | .131 | .503 | -.612 | .130 | .076 | -.140 | -.115 |
| v7 | -.091 | -.236 | .063 | .227 | -.528 | -.439 | -.230 | .240 |
| v8 | -.318 | .010 | -.048 | -.248 | -.445 | -.162 | -.337 | -.300 |
| v9 | -.203 | -.302 | -.115 | -.713 | -.142 | .164 | .011 | .269 |
+-----+-------+-------+-------+-------+-------+-------+-------+-------+
Traditional Kaiser criterion (k>1) returns 8 factors
== Parallel Analysis
Bootstrap Method: random
Uses SMC: No
Correlation Matrix type : correlation_matrix
Number of variables: 30
Number of cases: 150
Number of iterations: 50
Number or factors to preserve: 4
Eigenvalues
+----+-----------------+----------------------+--------+-----------+
| n | data eigenvalue | generated eigenvalue | p.95 | preserve? |
+----+-----------------+----------------------+--------+-----------+
| 1 | 11.6353 | 1.9397 | 2.0744 | Yes |
| 2 | 2.2275 | 1.7961 | 1.8770 | Yes |
| 3 | 1.8675 | 1.6885 | 1.7637 | Yes |
| 4 | 1.7809 | 1.6032 | 1.6780 | Yes |
| 5 | 1.5027 | 1.5281 | 1.5856 | |
| 6 | 1.2750 | 1.4573 | 1.5253 | |
| 7 | 1.1491 | 1.3892 | 1.4417 | |
| 8 | 1.0086 | 1.3263 | 1.3981 | |
| 9 | 0.9485 | 1.2711 | 1.3060 | |
| 10 | 0.8126 | 1.2174 | 1.2501 | |
| 11 | 0.7756 | 1.1585 | 1.2080 | |
| 12 | 0.6877 | 1.1053 | 1.1429 | |
| 13 | 0.5836 | 1.0553 | 1.0955 | |
| 14 | 0.5158 | 1.0083 | 1.0468 | |
| 15 | 0.4899 | 0.9635 | 1.0054 | |
| 16 | 0.4537 | 0.9161 | 0.9573 | |
| 17 | 0.4164 | 0.8739 | 0.9153 | |
| 18 | 0.3446 | 0.8270 | 0.8561 | |
| 19 | 0.3220 | 0.7909 | 0.8310 | |
| 20 | 0.2756 | 0.7524 | 0.7944 | |
| 21 | 0.2400 | 0.7086 | 0.7465 | |
| 22 | 0.2056 | 0.6678 | 0.7227 | |
| 23 | 0.1316 | 0.6309 | 0.6700 | |
| 24 | 0.0982 | 0.5889 | 0.6263 | |
| 25 | 0.0946 | 0.5534 | 0.5885 | |
| 26 | 0.0645 | 0.5173 | 0.5562 | |
| 27 | 0.0501 | 0.4795 | 0.5195 | |
| 28 | 0.0300 | 0.4405 | 0.4791 | |
| 29 | 0.0101 | 0.3978 | 0.4305 | |
| 30 | 0.0029 | 0.3470 | 0.3938 | |
+----+-----------------+----------------------+--------+-----------+
Parallel Analysis returns 4 factors to preserve