IBM SPSS Web Report - 10 variables 279 cases 3 factors.spv   


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Log
Log - Log - February 11, 2020

FACTOR
  /VARIABLES K1a K1b K1c K1d K1e K2a K2b K2c K2d K2e
  /MISSING LISTWISE
  /ANALYSIS K1a K1b K1c K1d K1e K2a K2b K2c K2d K2e
  /PRINT UNIVARIATE INITIAL EXTRACTION ROTATION FSCORE
  /PLOT EIGEN ROTATION
  /CRITERIA MINEIGEN(1) ITERATE(25)
  /EXTRACTION PC
  /CRITERIA ITERATE(25)
  /ROTATION VARIMAX
  /METHOD=COVARIANCE.

Factor Analysis
Factor Analysis - Descriptive Statistics - February 11, 2020
Descriptive StatisticsDescriptive Statistics, table, 1 levels of column headers and 1 levels of row headers, table with 4 columns and 12 rows
  Mean Std. Deviation Analysis N
K1a Lending money to family members .45 .498 279
K1b Lending money to relatives .48 .501 279
K1c Lending money to people in your own village .39 .488 279
K1d Lending money to people outside the village .16 .368 279
K1e Lending money to people from the same mosque/ church .17 .375 279
K2a Lending tools like axes, hoes etc. to family members .71 .455 279
K2b Lending tools like axes, hoes etc. to relatives outside the household .73 .442 279
K2c Lending tools like axes, hoes etc. to people in your own village .66 .475 279
K2d Lending tools like axes, hoes etc. to people outside the village .23 .421 279
K2e Lending tools like axes, hoes etc. to people from the same mosque/ church .29 .453 279
Factor Analysis
Factor Analysis - Communalities - February 11, 2020
CommunalitiesCommunalities, table, 2 levels of column headers and 1 levels of row headers, table with 5 columns and 14 rows
  Raw Rescaled
Initial Extraction Initial Extraction
K1a Lending money to family members .248 .190 1.000 .766
K1b Lending money to relatives .251 .191 1.000 .761
K1c Lending money to people in your own village .238 .177 1.000 .743
K1d Lending money to people outside the village .136 .063 1.000 .461
K1e Lending money to people from the same mosque/ church .141 .074 1.000 .524
K2a Lending tools like axes, hoes etc. to family members .207 .161 1.000 .779
K2b Lending tools like axes, hoes etc. to relatives outside the household .196 .127 1.000 .649
K2c Lending tools like axes, hoes etc. to people in your own village .225 .124 1.000 .550
K2d Lending tools like axes, hoes etc. to people outside the village .177 .123 1.000 .695
K2e Lending tools like axes, hoes etc. to people from the same mosque/ church .205 .144 1.000 .700
Extraction Method: Principal Component Analysis.
Factor Analysis
Factor Analysis - Total Variance Explained - February 11, 2020
Total Variance ExplainedTotal Variance Explained, table, 2 levels of column headers and 2 levels of row headers, table with 11 columns and 25 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 .813 40.193 40.193 .813 40.193 40.193 .592 29.237 29.237
2 .340 16.792 56.986 .340 16.792 56.986 .376 18.556 47.793
3 .220 10.859 67.845 .220 10.859 67.845 .406 20.052 67.845
4 .142 7.009 74.854            
5 .123 6.073 80.927            
6 .112 5.532 86.459            
7 .094 4.631 91.090            
8 .076 3.749 94.839            
9 .054 2.691 97.530            
10 .050 2.470 100.000            
Rescaled 1 .813 40.193 40.193 3.827 38.274 38.274 2.715 27.145 27.145
2 .340 16.792 56.986 1.596 15.955 54.229 1.996 19.964 47.109
3 .220 10.859 67.845 1.205 12.054 66.284 1.918 19.175 66.284
4 .142 7.009 74.854            
5 .123 6.073 80.927            
6 .112 5.532 86.459            
7 .094 4.631 91.090            
8 .076 3.749 94.839            
9 .054 2.691 97.530            
10 .050 2.470 100.000            
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 11, 2020
Scree Plot Component Number: 10
Eigenvalue: 0.0500 Component Number: 9
Eigenvalue: 0.0545 Component Number: 8
Eigenvalue: 0.0759 Component Number: 7
Eigenvalue: 0.0937 Component Number: 6
Eigenvalue: 0.1119 Component Number: 5
Eigenvalue: 0.1229 Component Number: 4
Eigenvalue: 0.1418 Component Number: 3
Eigenvalue: 0.2198 Component Number: 2
Eigenvalue: 0.3398 Component Number: 1
Eigenvalue: 0.8134 Component Number: 9
Eigenvalue: 0.0545 Component Number: 8
Eigenvalue: 0.0759 Component Number: 7
Eigenvalue: 0.0937 Component Number: 6
Eigenvalue: 0.1119 Component Number: 5
Eigenvalue: 0.1229 Component Number: 4
Eigenvalue: 0.1418 Component Number: 3
Eigenvalue: 0.2198 Component Number: 2
Eigenvalue: 0.3398 Component Number: 1
Eigenvalue: 0.8134 0.0 0.2 0.4 0.6 0.8 1.0 1 2 3 4 5 6 7 8 9 10

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Factor Analysis
Factor Analysis - Component Matrix - February 11, 2020
Component MatrixaComponent Matrix, table, 3 levels of column headers and 1 levels of row headers, table with 7 columns and 16 rows
  Raw Rescaled
Component Component
1 2 3 1 2 3
K1a Lending money to family members .385 -.185 -.087 .773 -.370 -.175
K1b Lending money to relatives .382 -.209 .030 .763 -.417 .060
K1c Lending money to people in your own village .358 -.203 .087 .734 -.416 .179
K1d Lending money to people outside the village .200 -.038 .146 .542 -.104 .396
K1e Lending money to people from the same mosque/ church .208 -.014 .173 .556 -.037 .463
K2a Lending tools like axes, hoes etc. to family members .276 .091 -.277 .607 .199 -.609
K2b Lending tools like axes, hoes etc. to relatives outside the household .266 .156 -.179 .601 .354 -.404
K2c Lending tools like axes, hoes etc. to people in your own village .279 .212 -.030 .588 .447 -.063
K2d Lending tools like axes, hoes etc. to people outside the village .190 .242 .170 .451 .574 .403
K2e Lending tools like axes, hoes etc. to people from the same mosque/ church .216 .288 .118 .477 .636 .261
Extraction Method: Principal Component Analysis.
a. 3 components extracted.
Factor Analysis
Factor Analysis - Rotated Component Matrix - February 11, 2020
Rotated Component MatrixaRotated Component Matrix, table, 3 levels of column headers and 1 levels of row headers, table with 7 columns and 16 rows
  Raw Rescaled
Component Component
1 2 3 1 2 3
K1a Lending money to family members .372 -.036 .225 .746 -.072 .452
K1b Lending money to relatives .418 .008 .124 .836 .016 .248
K1c Lending money to people in your own village .414 .034 .068 .848 .070 .139
K1d Lending money to people outside the village .215 .128 -.017 .582 .346 -.047
K1e Lending money to people from the same mosque/ church .215 .164 -.027 .572 .438 -.072
K2a Lending tools like axes, hoes etc. to family members .069 .025 .395 .153 .054 .868
K2b Lending tools like axes, hoes etc. to relatives outside the household .051 .123 .330 .116 .278 .747
K2c Lending tools like axes, hoes etc. to people in your own village .072 .251 .237 .151 .528 .499
K2d Lending tools like axes, hoes etc. to people outside the village .047 .346 .040 .111 .821 .094
K2e Lending tools like axes, hoes etc. to people from the same mosque/ church .023 .363 .107 .051 .801 .237
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.
Factor Analysis
Factor Analysis - Component Transformation Matrix - February 11, 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 .744 .387 .545
2 -.599 .747 .288
3 .295 .541 -.788
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
Factor Analysis
Factor Analysis - Component Plot of Factors 1, 2, 3 - February 11, 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: 0.1526
Component 2: 0.0539
Component 3: 0.8677 Component 1: 0.7458
Component 2: -0.0723
Component 3: 0.4520 Component 1: 0.1159
Component 2: 0.2781
Component 3: 0.7471 Component 1: 0.8359
Component 2: 0.0159
Component 3: 0.2483 Component 1: 0.8478
Component 2: 0.0699
Component 3: 0.1391 Component 1: 0.1511
Component 2: 0.5278
Component 3: 0.4986 Component 1: 0.0509
Component 2: 0.8008
Component 3: 0.2372 Component 1: 0.5824
Component 2: 0.3462
Component 3: -0.0468 Component 1: 0.5721
Component 2: 0.4378
Component 3: -0.0722 Component 1: 0.1108
Component 2: 0.8211
Component 3: 0.0942

Factor Analysis
Factor Analysis - Component Score Coefficient Matrix - February 11, 2020
Component Score Coefficient MatrixaComponent Score Coefficient Matrix, table, 2 levels of column headers and 1 levels of row headers, table with 4 columns and 15 rows
  Component
1 2 3
K1a Lending money to family members .279 -.218 .206
K1b Lending money to relatives .380 -.102 -.014
K1c Lending money to people in your own village .391 -.030 -.119
K1d Lending money to people outside the village .164 .136 -.155
K1e Lending money to people from the same mosque/ church .168 .186 -.185
K2a Lending tools like axes, hoes etc. to family members -.127 -.160 .570
K2b Lending tools like axes, hoes etc. to relatives outside the household -.121 .014 .420
K2c Lending tools like axes, hoes etc. to people in your own village -.075 .250 .225
K2d Lending tools like axes, hoes etc. to people outside the village -.010 .438 -.116
K2e Lending tools like axes, hoes etc. to people from the same mosque/ church -.069 .466 -.016
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Coefficients are standardized.
Factor Analysis
Factor Analysis - Component Score Covariance Matrix - February 11, 2020
Component Score Covariance MatrixComponent Score Covariance 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 1.000 .000 .000
2 .000 1.000 .000
3 .000 .000 1.000
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.