IBM SPSS Web Report - M3 variables 266 cases varimax rotated 2 factor.spv   


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Log
Log - Log - February 13, 2020

FACTOR
  /VARIABLES M3aFamil M3bRelatives M3cOwnVil M3dOutsideV M3eSameEthnic M3fOutsEthn M3gSameChM
    M3hNotSameChM
  /MISSING LISTWISE
  /ANALYSIS M3aFamil M3bRelatives M3cOwnVil M3dOutsideV M3eSameEthnic M3fOutsEthn M3gSameChM
    M3hNotSameChM
  /PRINT UNIVARIATE INITIAL EXTRACTION ROTATION
  /PLOT EIGEN ROTATION
  /CRITERIA MINEIGEN(1) ITERATE(25)
  /EXTRACTION PC
  /CRITERIA ITERATE(25)
  /ROTATION VARIMAX
  /METHOD=COVARIANCE.

Factor Analysis
Factor Analysis - Descriptive Statistics - February 13, 2020
Descriptive StatisticsDescriptive Statistics, table, 1 levels of column headers and 1 levels of row headers, table with 4 columns and 10 rows
  Mean Std. Deviation Analysis N
M3.a. Trust in family members 4.40 .935 266
M3.b. Trust in relatives 3.88 1.136 266
M3.c. Trust in people in own village 3.31 1.090 266
M3.d. Trust in people outside the village 2.72 1.118 266
M3.e. Trust in people of same ethnic group 3.10 1.082 266
M3.f. Trust in people outside ethnic group 2.74 1.098 266
M3.g. Trust in people from same church/ mosque 3.61 1.062 266
M3.h. Trust in people not from same church/ mosque 2.98 1.197 266
Factor Analysis
Factor Analysis - Communalities - February 13, 2020
CommunalitiesCommunalities, table, 2 levels of column headers and 1 levels of row headers, table with 5 columns and 12 rows
  Raw Rescaled
Initial Extraction Initial Extraction
M3.a. Trust in family members .875 .487 1.000 .557
M3.b. Trust in relatives 1.291 1.004 1.000 .777
M3.c. Trust in people in own village 1.188 .733 1.000 .617
M3.d. Trust in people outside the village 1.251 .741 1.000 .592
M3.e. Trust in people of same ethnic group 1.171 .859 1.000 .734
M3.f. Trust in people outside ethnic group 1.206 .919 1.000 .762
M3.g. Trust in people from same church/ mosque 1.129 .602 1.000 .533
M3.h. Trust in people not from same church/ mosque 1.433 .984 1.000 .687
Extraction Method: Principal Component Analysis.
Factor Analysis
Factor Analysis - Total Variance Explained - February 13, 2020
Total Variance ExplainedTotal Variance Explained, table, 2 levels of column headers and 2 levels of row headers, table with 11 columns and 21 rows
  Component Initial Eigenvaluesa Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
  Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %
Raw 1 5.072 53.147 53.147 5.072 53.147 53.147 3.775 39.562 39.562
2 1.257 13.167 66.314 1.257 13.167 66.314 2.553 26.752 66.314
3 .943 9.878 76.193            
4 .585 6.127 82.320            
5 .503 5.269 87.589            
6 .452 4.734 92.323            
7 .399 4.176 96.500            
8 .334 3.500 100.000            
Rescaled 1 5.072 53.147 53.147 4.190 52.377 52.377 3.027 37.838 37.838
2 1.257 13.167 66.314 1.069 13.361 65.738 2.232 27.901 65.738
3 .943 9.878 76.193            
4 .585 6.127 82.320            
5 .503 5.269 87.589            
6 .452 4.734 92.323            
7 .399 4.176 96.500            
8 .334 3.500 100.000            
Extraction Method: Principal Component Analysis.
a. When analyzing a covariance matrix, the initial eigenvalues are the same across the raw and rescaled solution.
Factor Analysis
Factor Analysis - Scree Plot - February 13, 2020
Scree Plot Component Number: 8
Eigenvalue: 0.3340 Component Number: 7
Eigenvalue: 0.3985 Component Number: 6
Eigenvalue: 0.4518 Component Number: 5
Eigenvalue: 0.5028 Component Number: 4
Eigenvalue: 0.5847 Component Number: 3
Eigenvalue: 0.9427 Component Number: 2
Eigenvalue: 1.2565 Component Number: 1
Eigenvalue: 5.0718 Component Number: 7
Eigenvalue: 0.3985 Component Number: 6
Eigenvalue: 0.4518 Component Number: 5
Eigenvalue: 0.5028 Component Number: 4
Eigenvalue: 0.5847 Component Number: 3
Eigenvalue: 0.9427 Component Number: 2
Eigenvalue: 1.2565 Component Number: 1
Eigenvalue: 5.0718 0 1 2 3 4 5 6 1 2 3 4 5 6 7 8

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Factor Analysis
Factor Analysis - Component Matrix - February 13, 2020
Component MatrixaComponent Matrix, table, 3 levels of column headers and 1 levels of row headers, table with 5 columns and 14 rows
  Raw Rescaled
Component Component
1 2 1 2
M3.a. Trust in family members .517 .469 .552 .502
M3.b. Trust in relatives .698 .719 .614 .633
M3.c. Trust in people in own village .839 .170 .770 .156
M3.d. Trust in people outside the village .769 -.387 .687 -.346
M3.e. Trust in people of same ethnic group .903 -.208 .835 -.192
M3.f. Trust in people outside ethnic group .905 -.316 .824 -.288
M3.g. Trust in people from same church/ mosque .723 .283 .680 .266
M3.h. Trust in people not from same church/ mosque .931 -.343 .778 -.287
Extraction Method: Principal Component Analysis.
a. 2 components extracted.
Factor Analysis
Factor Analysis - Rotated Component Matrix - February 13, 2020
Rotated Component MatrixaRotated Component Matrix, table, 3 levels of column headers and 1 levels of row headers, table with 5 columns and 14 rows
  Raw Rescaled
Component Component
1 2 1 2
M3.a. Trust in family members .146 .682 .156 .730
M3.b. Trust in relatives .148 .991 .130 .872
M3.c. Trust in people in own village .582 .627 .534 .575
M3.d. Trust in people outside the village .850 .133 .760 .119
M3.e. Trust in people of same ethnic group .855 .358 .790 .331
M3.f. Trust in people outside ethnic group .919 .271 .837 .246
M3.g. Trust in people from same church/ mosque .423 .651 .398 .613
M3.h. Trust in people not from same church/ mosque .956 .264 .799 .220
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 3 iterations.
Factor Analysis
Factor Analysis - Component Transformation Matrix - February 13, 2020
Component Transformation MatrixComponent Transformation Matrix, table, 1 levels of column headers and 1 levels of row headers, table with 3 columns and 5 rows
Component 1 2
1 .813 .583
2 -.583 .813
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
Factor Analysis
Factor Analysis - Component Plot of Factors 1, 2 - February 13, 2020
Component Plot of Factors 1, 2 Component 1: 0.7989
Component 2: 0.2204 Component 1: 0.3977
Component 2: 0.6126 Component 1: 0.8373
Component 2: 0.2464 Component 1: 0.7902
Component 2: 0.3306 Component 1: 0.7604
Component 2: 0.1191 Component 1: 0.5344
Component 2: 0.5755 Component 1: 0.1303
Component 2: 0.8720 Component 1: 0.1563
Component 2: 0.7297 -1.0 -0.5 0.0 0.5 1.0 -1.0 -0.5 0.0 0.5 1.0

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