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Parallel Factor Analysis for Batch 1,2,3,4 MapIt originality_raw
Raw
gistfile1.md

Intro

Couldn't do for all batches combined with 12 tasks. Because "horizontal" order is not kept between "Batch n" tests.

Batch 1 - originality_raw

MapIt: place: [0, 0, 100, 8, 0, 0, 0, 44, 0, 0, 0, 0, 0, 0, 2, 0, 0, 3, 0, 0, 0] ...
MapIt: laugh: [100, 63, 91, 0, 0, 91, 56, 0, 56, 0, 0, 91, 0, 56, 5, 0, 63, 0, 5, 19, 10] ...
MapIt: story: [0, 0, 100, 83, 0, 0, 1, 28, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0] ...

Analysis 2014-07-06 12:24:07 -0700
= Statsample::Factor::ParallelAnalysis
  There are 3 real factors on data
  == Principal Component Analysis
    Number of factors: 2
    Communalities
+--------------+---------+------------+--------+
|   Variable   | Initial | Extraction |   %    |
+--------------+---------+------------+--------+
| MapIt: laugh | 1.000   | 0.998      | 99.760 |
| MapIt: place | 1.000   | 0.864      | 86.392 |
| MapIt: story | 1.000   | 0.863      | 86.295 |
+--------------+---------+------------+--------+

    Total Variance Explained
+-------------+---------+---------+---------+
|  Component  | E.Total |    %    | Cum. %  |
+-------------+---------+---------+---------+
| Component 1 | 1.719   | 57.305% | 57.305  |
| Component 2 | 1.005   | 33.511% | 90.816  |
| Component 3 | 0.276   | 9.184%  | 100.000 |
+-------------+---------+---------+---------+

    Component matrix
+--------------+-------+-------+
|              | PC_1  | PC_2  |
+--------------+-------+-------+
| MapIt: laugh | -.050 | .998  |
| MapIt: place | .925  | .093  |
| MapIt: story | .928  | -.039 |
+--------------+-------+-------+

  Traditional Kaiser criterion (k>1) returns 2 factors
  == Parallel Analysis
    Bootstrap Method: random
    Uses SMC: No
    Correlation Matrix type : correlation_matrix
    Number of variables: 3
    Number of cases: 116
    Number of iterations: 50
    Number or factors to preserve: 1
    Eigenvalues
+---+-----------------+----------------------+--------+-----------+
| n | data eigenvalue | generated eigenvalue |  p.95  | preserve? |
+---+-----------------+----------------------+--------+-----------+
| 1 | 1.7191          | 1.1447               | 1.2741 | Yes       |
| 2 | 1.0053          | 0.9982               | 1.0575 |           |
| 3 | 0.2755          | 0.8571               | 0.9384 |           |
+---+-----------------+----------------------+--------+-----------+

  Parallel Analysis returns 1 factors to preserve

Batch 2 - originality_raw

MapIt: creation: [100, 86, 15, 100, 100, 7, 9, 18, 3, 4, 43, 11, 17, 41, 13, 15, 14, 3, 2, 9, 5] ...
MapIt: song: [2, 100, 3, 4, 3, 7, 1, 25, 12, 1, 87, 3, 1, 4, 31, 58, 22, 1, 0, 5, 6] ...
MapIt: stop: [14, 100, 100, 45, 14, 6, 15, 53, 31, 4, 60, 1, 4, 29, 1, 12, 12, 1, 1, 11, 4] ...

Analysis 2014-07-06 12:26:12 -0700
= Statsample::Factor::ParallelAnalysis
  There are 3 real factors on data
  == Principal Component Analysis
    Number of factors: 1
    Communalities
+-----------------+---------+------------+--------+
|    Variable     | Initial | Extraction |   %    |
+-----------------+---------+------------+--------+
| MapIt: creation | 1.000   | 0.375      | 37.521 |
| MapIt: song     | 1.000   | 0.301      | 30.148 |
| MapIt: stop     | 1.000   | 0.666      | 66.595 |
+-----------------+---------+------------+--------+

    Total Variance Explained
+-------------+---------+---------+---------+
|  Component  | E.Total |    %    | Cum. %  |
+-------------+---------+---------+---------+
| Component 1 | 1.343   | 44.754% | 44.754  |
| Component 2 | 0.995   | 33.152% | 77.907  |
| Component 3 | 0.663   | 22.093% | 100.000 |
+-------------+---------+---------+---------+

    Component matrix
+-----------------+------+
|                 | PC_1 |
+-----------------+------+
| MapIt: creation | .613 |
| MapIt: song     | .549 |
| MapIt: stop     | .816 |
+-----------------+------+

  Traditional Kaiser criterion (k>1) returns 1 factors
  == Parallel Analysis
    Bootstrap Method: random
    Uses SMC: No
    Correlation Matrix type : correlation_matrix
    Number of variables: 3
    Number of cases: 101
    Number of iterations: 50
    Number or factors to preserve: 1
    Eigenvalues
+---+-----------------+----------------------+--------+-----------+
| n | data eigenvalue | generated eigenvalue |  p.95  | preserve? |
+---+-----------------+----------------------+--------+-----------+
| 1 | 1.3426          | 1.1609               | 1.2936 | Yes       |
| 2 | 0.9946          | 0.9922               | 1.0570 |           |
| 3 | 0.6628          | 0.8470               | 0.9506 |           |
+---+-----------------+----------------------+--------+-----------+

  Parallel Analysis returns 1 factors to preserve

Batch 3 - originality_raw

MapIt: flower: [24, 46, 26, 33, 43, 97, 56, 57, 46, 33, 14, 33, 53, 39, 26, 19, 18, 29, 40, 79, 25] ...
MapIt: star: [8, 53, 17, 5, 19, 17, 47, 94, 7, 6, 10, 89, 32, 47, 18, 6, 7, 6, 2, 31, 6] ...
MapIt: smoke: [72, 33, 52, 94, 2, 99, 99, 82, 33, 23, 45, 80, 45, 77, 56, 17, 13, 56, 17, 87, 63] ...

Analysis 2014-07-06 12:26:38 -0700
= Statsample::Factor::ParallelAnalysis
  There are 3 real factors on data
  == Principal Component Analysis
    Number of factors: 1
    Communalities
+---------------+---------+------------+--------+
|   Variable    | Initial | Extraction |   %    |
+---------------+---------+------------+--------+
| MapIt: flower | 1.000   | 0.616      | 61.624 |
| MapIt: smoke  | 1.000   | 0.409      | 40.863 |
| MapIt: star   | 1.000   | 0.364      | 36.394 |
+---------------+---------+------------+--------+

    Total Variance Explained
+-------------+---------+---------+---------+
|  Component  | E.Total |    %    | Cum. %  |
+-------------+---------+---------+---------+
| Component 1 | 1.389   | 46.294% | 46.294  |
| Component 2 | 0.922   | 30.718% | 77.011  |
| Component 3 | 0.690   | 22.989% | 100.000 |
+-------------+---------+---------+---------+

    Component matrix
+---------------+------+
|               | PC_1 |
+---------------+------+
| MapIt: flower | .785 |
| MapIt: smoke  | .639 |
| MapIt: star   | .603 |
+---------------+------+

  Traditional Kaiser criterion (k>1) returns 1 factors
  == Parallel Analysis
    Bootstrap Method: random
    Uses SMC: No
    Correlation Matrix type : correlation_matrix
    Number of variables: 3
    Number of cases: 103
    Number of iterations: 50
    Number or factors to preserve: 1
    Eigenvalues
+---+-----------------+----------------------+--------+-----------+
| n | data eigenvalue | generated eigenvalue |  p.95  | preserve? |
+---+-----------------+----------------------+--------+-----------+
| 1 | 1.3888          | 1.1546               | 1.2549 | Yes       |
| 2 | 0.9215          | 0.9946               | 1.0545 |           |
| 3 | 0.6897          | 0.8508               | 0.9258 |           |
+---+-----------------+----------------------+--------+-----------+

  Parallel Analysis returns 1 factors to preserve

Batch 4 - originality_raw

MapIt: company: [41, 36, 7, 10, 12, 24, 16, 24, 3, 4, 8, 49, 20, 63, 8, 17, 4, 3, 10, 5, 2] ...
MapIt: moon: [63, 3, 31, 12, 4, 27, 17, 18, 48, 21, 14, 38, 53, 66, 55, 45, 19, 30, 29, 44, 80] ...
MapIt: cat: [42, 46, 74, 40, 12, 99, 33, 48, 46, 37, 85, 86, 55, 64, 38, 41, 70, 44, 99, 10, 82] ...

Analysis 2014-07-06 12:27:03 -0700
= Statsample::Factor::ParallelAnalysis
  There are 3 real factors on data
  == Principal Component Analysis
    Number of factors: 1
    Communalities
+----------------+---------+------------+--------+
|    Variable    | Initial | Extraction |   %    |
+----------------+---------+------------+--------+
| MapIt: cat     | 1.000   | 0.467      | 46.736 |
| MapIt: company | 1.000   | 0.406      | 40.557 |
| MapIt: moon    | 1.000   | 0.571      | 57.102 |
+----------------+---------+------------+--------+

    Total Variance Explained
+-------------+---------+---------+---------+
|  Component  | E.Total |    %    | Cum. %  |
+-------------+---------+---------+---------+
| Component 1 | 1.444   | 48.131% | 48.131  |
| Component 2 | 0.849   | 28.287% | 76.419  |
| Component 3 | 0.707   | 23.581% | 100.000 |
+-------------+---------+---------+---------+

    Component matrix
+----------------+------+
|                | PC_1 |
+----------------+------+
| MapIt: cat     | .684 |
| MapIt: company | .637 |
| MapIt: moon    | .756 |
+----------------+------+

  Traditional Kaiser criterion (k>1) returns 1 factors
  == Parallel Analysis
    Bootstrap Method: random
    Uses SMC: No
    Correlation Matrix type : correlation_matrix
    Number of variables: 3
    Number of cases: 136
    Number of iterations: 50
    Number or factors to preserve: 1
    Eigenvalues
+---+-----------------+----------------------+--------+-----------+
| n | data eigenvalue | generated eigenvalue |  p.95  | preserve? |
+---+-----------------+----------------------+--------+-----------+
| 1 | 1.4439          | 1.1443               | 1.2544 | Yes       |
| 2 | 0.8486          | 1.0016               | 1.0728 |           |
| 3 | 0.7074          | 0.8541               | 0.9415 |           |
+---+-----------------+----------------------+--------+-----------+

  Parallel Analysis returns 1 factors to preserve
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