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


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Log
Log - Log - February 13, 2020

FACTOR
  /VARIABLES M2aGovBIN M2bCounBIN M2cAssemBIN M2dTradBIN M2eGVHBIN M2fVHBIN M2gCourtBIN M2hArmyBIN
    M2iNGOBIN M2jPoliceBIN M2kTradeBIN M2lTeachBIN M2mSchABIN M2nRelLeBIN
  /MISSING LISTWISE
  /ANALYSIS M2aGovBIN M2bCounBIN M2cAssemBIN M2dTradBIN M2eGVHBIN M2fVHBIN M2gCourtBIN M2hArmyBIN
    M2iNGOBIN M2jPoliceBIN M2kTradeBIN M2lTeachBIN M2mSchABIN M2nRelLeBIN
  /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 .52 .501 174
M2.b. Trust in councillors .32 .466 174
M2.c. Trust in local assembly staff .40 .491 174
M2.d. Trust in Traditional Authorities .65 .479 174
M2.e. Trust in group village headmen .63 .484 174
M2.f. Trust in village headmen .61 .489 174
M2.g. Trust in courts .63 .485 174
M2.h. Trust in army .75 .436 174
M2.i. Trust in leaders of NGOs .53 .500 174
M2.j. Trust in police .59 .493 174
M2.k. Trust in traders .24 .429 174
M2.l. Trust in teachers .65 .479 174
M2.m.Trust in school administrators .65 .479 174
M2.n. Trust in religious leaders .67 .473 174
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 .251 .131 1.000 .521
M2.b. Trust in councillors .217 .162 1.000 .747
M2.c. Trust in local assembly staff .241 .198 1.000 .823
M2.d. Trust in Traditional Authorities .229 .170 1.000 .745
M2.e. Trust in group village headmen .234 .181 1.000 .774
M2.f. Trust in village headmen .239 .177 1.000 .741
M2.g. Trust in courts .235 .097 1.000 .412
M2.h. Trust in army .190 .116 1.000 .609
M2.i. Trust in leaders of NGOs .250 .151 1.000 .602
M2.j. Trust in police .243 .171 1.000 .703
M2.k. Trust in traders .184 .066 1.000 .356
M2.l. Trust in teachers .229 .113 1.000 .495
M2.m.Trust in school administrators .229 .105 1.000 .458
M2.n. Trust in religious leaders .224 .104 1.000 .464
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 1.362 42.607 42.607 1.362 42.607 42.607 .869 27.202 27.202
2 .303 9.492 52.099 .303 9.492 52.099 .540 16.890 44.092
3 .277 8.659 60.758 .277 8.659 60.758 .533 16.666 60.758
4 .217 6.802 67.560            
5 .179 5.610 73.170            
6 .152 4.746 77.916            
7 .138 4.329 82.244            
8 .123 3.848 86.092            
9 .107 3.358 89.450            
10 .098 3.060 92.509            
11 .077 2.397 94.907            
12 .071 2.221 97.128            
13 .051 1.608 98.736            
14 .040 1.264 100.000            
Rescaled 1 1.362 42.607 42.607 5.904 42.171 42.171 3.731 26.650 26.650
2 .303 9.492 52.099 1.324 9.460 51.631 2.403 17.163 43.813
3 .277 8.659 60.758 1.220 8.716 60.347 2.315 16.534 60.347
4 .217 6.802 67.560            
5 .179 5.610 73.170            
6 .152 4.746 77.916            
7 .138 4.329 82.244            
8 .123 3.848 86.092            
9 .107 3.358 89.450            
10 .098 3.060 92.509            
11 .077 2.397 94.907            
12 .071 2.221 97.128            
13 .051 1.608 98.736            
14 .040 1.264 100.000            
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: 0.0404 Component Number: 13
Eigenvalue: 0.0514 Component Number: 12
Eigenvalue: 0.0710 Component Number: 11
Eigenvalue: 0.0766 Component Number: 10
Eigenvalue: 0.0978 Component Number: 9
Eigenvalue: 0.1073 Component Number: 8
Eigenvalue: 0.1230 Component Number: 7
Eigenvalue: 0.1383 Component Number: 6
Eigenvalue: 0.1517 Component Number: 5
Eigenvalue: 0.1793 Component Number: 4
Eigenvalue: 0.2174 Component Number: 3
Eigenvalue: 0.2767 Component Number: 2
Eigenvalue: 0.3034 Component Number: 1
Eigenvalue: 1.3616 Component Number: 13
Eigenvalue: 0.0514 Component Number: 12
Eigenvalue: 0.0710 Component Number: 11
Eigenvalue: 0.0766 Component Number: 10
Eigenvalue: 0.0978 Component Number: 9
Eigenvalue: 0.1073 Component Number: 8
Eigenvalue: 0.1230 Component Number: 7
Eigenvalue: 0.1383 Component Number: 6
Eigenvalue: 0.1517 Component Number: 5
Eigenvalue: 0.1793 Component Number: 4
Eigenvalue: 0.2174 Component Number: 3
Eigenvalue: 0.2767 Component Number: 2
Eigenvalue: 0.3034 Component Number: 1
Eigenvalue: 1.3616 0.00 0.25 0.50 0.75 1.00 1.25 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 .339 -.122 .023 .677 -.244 .046
M2.b. Trust in councillors .281 -.210 .199 .603 -.449 .426
M2.c. Trust in local assembly staff .296 -.245 .224 .603 -.500 .457
M2.d. Trust in Traditional Authorities .358 -.149 -.142 .749 -.310 -.296
M2.e. Trust in group village headmen .383 -.058 -.175 .793 -.120 -.361
M2.f. Trust in village headmen .387 -.041 -.161 .791 -.084 -.330
M2.g. Trust in courts .308 -.006 -.048 .634 -.012 -.099
M2.h. Trust in army .224 .188 .175 .513 .431 .401
M2.i. Trust in leaders of NGOs .253 .220 .196 .506 .439 .392
M2.j. Trust in police .371 .166 .075 .753 .336 .153
M2.k. Trust in traders .238 .013 .094 .554 .031 .219
M2.l. Trust in teachers .300 .085 -.126 .627 .177 -.264
M2.m.Trust in school administrators .279 .152 -.060 .584 .318 -.126
M2.n. Trust in religious leaders .289 .126 -.067 .611 .265 -.141
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 .239 .086 .258 .477 .171 .514
M2.b. Trust in councillors .080 .082 .387 .171 .175 .829
M2.c. Trust in local assembly staff .074 .076 .432 .151 .155 .881
M2.d. Trust in Traditional Authorities .364 -.006 .194 .761 -.013 .406
M2.e. Trust in group village headmen .402 .055 .126 .832 .113 .261
M2.f. Trust in village headmen .396 .075 .123 .809 .154 .252
M2.g. Trust in courts .260 .119 .124 .536 .246 .255
M2.h. Trust in army .043 .330 .072 .098 .756 .165
M2.i. Trust in leaders of NGOs .049 .378 .076 .099 .755 .152
M2.j. Trust in police .219 .335 .103 .444 .680 .208
M2.k. Trust in traders .112 .170 .155 .261 .396 .361
M2.l. Trust in teachers .305 .142 .015 .637 .297 .031
M2.m.Trust in school administrators .243 .214 -.006 .508 .447 -.012
M2.n. Trust in religious leaders .255 .196 .014 .539 .415 .029
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 7 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 .739 .479 .473
2 -.027 .724 -.690
3 -.673 .497 .548
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: 0.1515
Component 2: 0.1547
Component 3: 0.8809 Component 1: 0.1714
Component 2: 0.1755
Component 3: 0.8289 Component 1: 0.7612
Component 2: -0.0133
Component 3: 0.4062 Component 1: 0.4765
Component 2: 0.1706
Component 3: 0.5141 Component 1: 0.8323
Component 2: 0.1134
Component 3: 0.2607 Component 1: 0.8085
Component 2: 0.1542
Component 3: 0.2518 Component 1: 0.5359
Component 2: 0.2458
Component 3: 0.2547 Component 1: 0.4444
Component 2: 0.6801
Component 3: 0.2081 Component 1: 0.2612
Component 2: 0.3965
Component 3: 0.3614 Component 1: 0.6366
Component 2: 0.2974
Component 3: 0.0306 Component 1: 0.5392
Component 2: 0.4147
Component 3: 0.0288 Component 1: 0.5076
Component 2: 0.4472
Component 3: -0.0120 Component 1: 0.0975
Component 2: 0.7563
Component 3: 0.1653 Component 1: 0.0986
Component 2: 0.7547
Component 3: 0.1517