IBM SPSS Web Report - M2 variables 174 cases varimax rotated 3 factor.spv   


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Log
Log - Log - February 13, 2020

FACTOR
  /VARIABLES M2aGovOff M2bCouncil M2cAssembly M2dTradAut M2eGVH M2fVH M2gCourts M2hArmy M2iNGO
    M2jPolice M2kTraders M2lTeacher M2mSchAdm M2nRelLead
  /MISSING LISTWISE
  /ANALYSIS M2aGovOff M2bCouncil M2cAssembly M2dTradAut M2eGVH M2fVH M2gCourts M2hArmy M2iNGO
    M2jPolice M2kTraders M2lTeacher M2mSchAdm M2nRelLead
  /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 16 rows
  Mean Std. Deviation Analysis N
M2.a. Trust in government officials 3.64 1.291 174
M2.b. Trust in councillors 2.94 1.376 174
M2.c. Trust in local assembly staff 3.21 1.395 174
M2.d. Trust in Traditional Authorities 3.97 1.195 174
M2.e. Trust in group village headmen 3.92 1.204 174
M2.f. Trust in village headmen 3.86 1.225 174
M2.g. Trust in courts 3.94 1.227 174
M2.h. Trust in army 4.20 1.064 174
M2.i. Trust in leaders of NGOs 3.60 1.294 174
M2.j. Trust in police 3.77 1.319 174
M2.k. Trust in traders 2.67 1.419 174
M2.l. Trust in teachers 4.00 1.143 174
M2.m.Trust in school administrators 3.89 1.170 174
M2.n. Trust in religious leaders 3.98 1.153 174
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 18 rows
  Raw Rescaled
Initial Extraction Initial Extraction
M2.a. Trust in government officials 1.666 .807 1.000 .485
M2.b. Trust in councillors 1.893 1.476 1.000 .780
M2.c. Trust in local assembly staff 1.945 1.600 1.000 .823
M2.d. Trust in Traditional Authorities 1.427 1.124 1.000 .788
M2.e. Trust in group village headmen 1.450 1.201 1.000 .828
M2.f. Trust in village headmen 1.499 1.179 1.000 .786
M2.g. Trust in courts 1.505 .745 1.000 .495
M2.h. Trust in army 1.133 .607 1.000 .536
M2.i. Trust in leaders of NGOs 1.675 1.063 1.000 .635
M2.j. Trust in police 1.739 1.120 1.000 .644
M2.k. Trust in traders 2.013 .964 1.000 .479
M2.l. Trust in teachers 1.306 .753 1.000 .576
M2.m.Trust in school administrators 1.370 .731 1.000 .534
M2.n. Trust in religious leaders 1.329 .651 1.000 .490
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 33 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 9.689 44.141 44.141 9.689 44.141 44.141 5.615 25.581 25.581
2 2.416 11.005 55.146 2.416 11.005 55.146 4.122 18.781 44.362
3 1.916 8.729 63.875 1.916 8.729 63.875 4.283 19.513 63.875
4 1.439 6.555 70.430            
5 1.241 5.653 76.084            
6 1.020 4.646 80.730            
7 .907 4.131 84.861            
8 .657 2.992 87.852            
9 .638 2.905 90.757            
10 .584 2.659 93.416            
11 .478 2.179 95.596            
12 .426 1.941 97.536            
13 .318 1.446 98.983            
14 .223 1.017 100.000            
Rescaled 1 9.689 44.141 44.141 6.193 44.239 44.239 3.816 27.258 27.258
2 2.416 11.005 55.146 1.408 10.054 54.293 2.723 19.451 46.709
3 1.916 8.729 63.875 1.276 9.115 63.408 2.338 16.698 63.408
4 1.439 6.555 70.430            
5 1.241 5.653 76.084            
6 1.020 4.646 80.730            
7 .907 4.131 84.861            
8 .657 2.992 87.852            
9 .638 2.905 90.757            
10 .584 2.659 93.416            
11 .478 2.179 95.596            
12 .426 1.941 97.536            
13 .318 1.446 98.983            
14 .223 1.017 100.000            
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: 14
Eigenvalue: 0.2233 Component Number: 13
Eigenvalue: 0.3175 Component Number: 12
Eigenvalue: 0.4260 Component Number: 11
Eigenvalue: 0.4784 Component Number: 10
Eigenvalue: 0.5837 Component Number: 9
Eigenvalue: 0.6376 Component Number: 8
Eigenvalue: 0.6567 Component Number: 7
Eigenvalue: 0.9068 Component Number: 6
Eigenvalue: 1.0198 Component Number: 5
Eigenvalue: 1.2409 Component Number: 4
Eigenvalue: 1.4389 Component Number: 3
Eigenvalue: 1.9161 Component Number: 2
Eigenvalue: 2.4155 Component Number: 1
Eigenvalue: 9.6890 Component Number: 13
Eigenvalue: 0.3175 Component Number: 12
Eigenvalue: 0.4260 Component Number: 11
Eigenvalue: 0.4784 Component Number: 10
Eigenvalue: 0.5837 Component Number: 9
Eigenvalue: 0.6376 Component Number: 8
Eigenvalue: 0.6567 Component Number: 7
Eigenvalue: 0.9068 Component Number: 6
Eigenvalue: 1.0198 Component Number: 5
Eigenvalue: 1.2409 Component Number: 4
Eigenvalue: 1.4389 Component Number: 3
Eigenvalue: 1.9161 Component Number: 2
Eigenvalue: 2.4155 Component Number: 1
Eigenvalue: 9.6890 0 2 4 6 8 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14

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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 7 columns and 20 rows
  Raw Rescaled
Component Component
1 2 3 1 2 3
M2.a. Trust in government officials .805 -.298 -.266 .624 -.231 -.206
M2.b. Trust in councillors .873 -.842 -.065 .635 -.612 -.047
M2.c. Trust in local assembly staff .859 -.927 .056 .616 -.665 .040
M2.d. Trust in Traditional Authorities .906 .102 -.542 .758 .085 -.454
M2.e. Trust in group village headmen .939 .321 -.464 .780 .267 -.385
M2.f. Trust in village headmen .965 .326 -.375 .788 .266 -.306
M2.g. Trust in courts .825 .151 -.204 .673 .123 -.166
M2.h. Trust in army .574 .149 .505 .540 .140 .474
M2.i. Trust in leaders of NGOs .650 .123 .791 .502 .095 .611
M2.j. Trust in police .986 .169 .346 .748 .128 .262
M2.k. Trust in traders .912 -.209 .296 .643 -.147 .209
M2.l. Trust in teachers .751 .432 .041 .657 .378 .036
M2.m.Trust in school administrators .787 .247 .226 .672 .211 .193
M2.n. Trust in religious leaders .698 .398 .081 .605 .345 .070
Extraction Method: Principal Component Analysis.
a. 3 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 7 columns and 20 rows
  Raw Rescaled
Component Component
1 2 3 1 2 3
M2.a. Trust in government officials .573 .133 .679 .444 .103 .526
M2.b. Trust in councillors .263 .191 1.171 .191 .139 .851
M2.c. Trust in local assembly staff .145 .259 1.230 .104 .186 .882
M2.d. Trust in Traditional Authorities .979 .067 .402 .820 .056 .336
M2.e. Trust in group village headmen 1.053 .205 .225 .874 .170 .187
M2.f. Trust in village headmen 1.020 .292 .230 .833 .238 .188
M2.g. Trust in courts .747 .311 .300 .609 .253 .245
M2.h. Trust in army .161 .750 .135 .151 .705 .127
M2.i. Trust in leaders of NGOs .033 1.015 .179 .026 .784 .139
M2.j. Trust in police .543 .845 .335 .411 .640 .254
M2.k. Trust in traders .356 .667 .626 .251 .470 .441
M2.l. Trust in teachers .677 .542 .007 .592 .475 .006
M2.m.Trust in school administrators .511 .663 .174 .437 .566 .149
M2.n. Trust in religious leaders .602 .537 .007 .522 .466 .006
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 5 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 4 columns and 6 rows
Component 1 2 3
1 .681 .529 .507
2 .439 .259 -.860
3 -.586 .808 -.056
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
Factor Analysis
Factor Analysis - Component Plot of Factors 1, 2, 3 - February 13, 2020
Component Plot of Factors 1, 2, 3 -1.0 -0.5 0.0 0.5 1.0 -1.0 -0.5 0.0 0.5 1.0 -1.0 -0.5 0.0 0.5 1.0 Component 1: 0.1912
Component 2: 0.1388
Component 3: 0.8508 Component 1: 0.1037
Component 2: 0.1856
Component 3: 0.8817 Component 1: 0.8197
Component 2: 0.0563
Component 3: 0.3361 Component 1: 0.4442
Component 2: 0.1031
Component 3: 0.5261 Component 1: 0.8741
Component 2: 0.1701
Component 3: 0.1872 Component 1: 0.8331
Component 2: 0.2382
Component 3: 0.1876 Component 1: 0.6091
Component 2: 0.2533
Component 3: 0.2446 Component 1: 0.2508
Component 2: 0.4704
Component 3: 0.4410 Component 1: 0.4114
Component 2: 0.6404
Component 3: 0.2543 Component 1: 0.4370
Component 2: 0.5662
Component 3: 0.1485 Component 1: 0.5924
Component 2: 0.4745
Component 3: 0.0058 Component 1: 0.5225
Component 2: 0.4659
Component 3: 0.0061 Component 1: 0.1510
Component 2: 0.7048
Component 3: 0.1266 Component 1: 0.0256
Component 2: 0.7841
Component 3: 0.1385