IBM SPSS Web Report - 30var PC varimax 7 factors.spv   


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Log
Log - Log - February 7, 2020

FACTOR
  /VARIABLES K1a K1b K1c K1d K1e K2a K2b L2 L3d L3e L3f L6 L7 M1trust M2dTradAut M2eGVH M2fVH
    M2jPolice M2kTraders M2lTeacher M2mSchAdm M2nRelLead M3aFamil M3bRelatives M3cOwnVil M3dOutsideV
    M3eSameEthnic M3fOutsEthn M3gSameChM M3hNotSameChM
  /MISSING LISTWISE
  /ANALYSIS K1a K1b K1c K1d K1e K2a K2b L2 L3d L3e L3f L6 L7 M1trust M2dTradAut M2eGVH M2fVH
    M2jPolice M2kTraders M2lTeacher M2mSchAdm M2nRelLead 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 7, 2020
Descriptive StatisticsDescriptive Statistics, table, 1 levels of column headers and 1 levels of row headers, table with 4 columns and 32 rows
  Mean Std. Deviation Analysis N
K1a Lending money to family members .43 .497 235
K1b Lending money to relatives .49 .501 235
K1c Lending money to people in your own village .39 .488 235
K1d Lending money to people outside the village .16 .365 235
K1e Lending money to people from the same mosque/ church .16 .365 235
K2a Lending tools like axes, hoes etc. to family members .71 .454 235
K2b Lending tools like axes, hoes etc. to relatives outside the household .76 .427 235
L2 Participated in cooperative agricultural work .41 .493 235
L3.d. Participated last 12 months in cooperative work of weeding .17 .377 235
L3.e. Participated last 12 months in cooperative work of harvesting .20 .401 235
L3.f. Participated last 12 months in cooperative work of other agriculture work .14 .348 235
L6 Participation in other exchange work than agriculture .52 .501 235
L7 Participated in public works without payment during the last year .80 .398 235
M1 Most people can be trusted (1) or you cannot be too careful (0) .46 .499 235
M2.d. Trust in Traditional Authorities 3.79 1.168 235
M2.e. Trust in group village headmen 3.69 1.196 235
M2.f. Trust in village headmen 3.70 1.207 235
M2.j. Trust in police 3.66 1.279 235
M2.k. Trust in traders 2.50 1.325 235
M2.l. Trust in teachers 3.85 1.095 235
M2.m.Trust in school administrators 3.71 1.173 235
M2.n. Trust in religious leaders 3.93 1.109 235
M3.a. Trust in family members 4.41 .936 235
M3.b. Trust in relatives 3.89 1.157 235
M3.c. Trust in people in own village 3.34 1.100 235
M3.d. Trust in people outside the village 2.72 1.120 235
M3.e. Trust in people of same ethnic group 3.13 1.096 235
M3.f. Trust in people outside ethnic group 2.79 1.120 235
M3.g. Trust in people from same church/ mosque 3.63 1.068 235
M3.h. Trust in people not from same church/ mosque 3.01 1.214 235
Factor Analysis
Factor Analysis - Communalities - February 7, 2020
CommunalitiesCommunalities, table, 2 levels of column headers and 1 levels of row headers, table with 5 columns and 34 rows
  Raw Rescaled
Initial Extraction Initial Extraction
K1a Lending money to family members .247 .110 1.000 .446
K1b Lending money to relatives .251 .103 1.000 .412
K1c Lending money to people in your own village .238 .091 1.000 .383
K1d Lending money to people outside the village .133 .021 1.000 .159
K1e Lending money to people from the same mosque/ church .133 .024 1.000 .179
K2a Lending tools like axes, hoes etc. to family members .207 .047 1.000 .228
K2b Lending tools like axes, hoes etc. to relatives outside the household .182 .031 1.000 .172
L2 Participated in cooperative agricultural work .243 .060 1.000 .247
L3.d. Participated last 12 months in cooperative work of weeding .142 .029 1.000 .204
L3.e. Participated last 12 months in cooperative work of harvesting .161 .032 1.000 .197
L3.f. Participated last 12 months in cooperative work of other agriculture work .121 .038 1.000 .316
L6 Participation in other exchange work than agriculture .251 .078 1.000 .312
L7 Participated in public works without payment during the last year .158 .050 1.000 .317
M1 Most people can be trusted (1) or you cannot be too careful (0) .249 .068 1.000 .272
M2.d. Trust in Traditional Authorities 1.365 1.127 1.000 .826
M2.e. Trust in group village headmen 1.430 1.257 1.000 .878
M2.f. Trust in village headmen 1.458 1.168 1.000 .801
M2.j. Trust in police 1.637 1.489 1.000 .910
M2.k. Trust in traders 1.755 1.667 1.000 .950
M2.l. Trust in teachers 1.199 .930 1.000 .776
M2.m.Trust in school administrators 1.376 1.065 1.000 .774
M2.n. Trust in religious leaders 1.230 .771 1.000 .627
M3.a. Trust in family members .876 .470 1.000 .536
M3.b. Trust in relatives 1.338 1.106 1.000 .827
M3.c. Trust in people in own village 1.210 .795 1.000 .657
M3.d. Trust in people outside the village 1.254 1.040 1.000 .829
M3.e. Trust in people of same ethnic group 1.200 .932 1.000 .776
M3.f. Trust in people outside ethnic group 1.254 .981 1.000 .782
M3.g. Trust in people from same church/ mosque 1.141 .939 1.000 .822
M3.h. Trust in people not from same church/ mosque 1.474 1.218 1.000 .826
Extraction Method: Principal Component Analysis.
Factor Analysis
Factor Analysis - Total Variance Explained - February 7, 2020
Total Variance ExplainedTotal Variance Explained, table, 2 levels of column headers and 2 levels of row headers, table with 11 columns and 65 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 9.571 40.025 40.025 9.571 40.025 40.025 4.421 18.487 18.487
2 2.245 9.390 49.415 2.245 9.390 49.415 1.319 5.517 24.003
3 1.577 6.596 56.010 1.577 6.596 56.010 3.810 15.935 39.939
4 1.451 6.066 62.077 1.451 6.066 62.077 2.959 12.374 52.313
5 1.053 4.406 66.482 1.053 4.406 66.482 1.731 7.239 59.552
6 .938 3.921 70.403 .938 3.921 70.403 1.531 6.403 65.955
7 .901 3.766 74.170 .901 3.766 74.170 1.964 8.214 74.170
8 .766 3.201 77.371            
9 .632 2.643 80.014            
10 .540 2.258 82.272            
11 .510 2.133 84.405            
12 .470 1.967 86.372            
13 .434 1.817 88.188            
14 .388 1.624 89.812            
15 .356 1.488 91.301            
16 .295 1.235 92.536            
17 .282 1.179 93.715            
18 .260 1.088 94.803            
19 .206 .860 95.663            
20 .182 .762 96.425            
21 .159 .663 97.088            
22 .142 .592 97.681            
23 .111 .464 98.145            
24 .086 .358 98.503            
25 .085 .355 98.858            
26 .076 .320 99.177            
27 .061 .255 99.432            
28 .051 .214 99.646            
29 .045 .186 99.833            
30 .040 .167 100.000            
Rescaled 1 9.571 40.025 40.025 7.386 24.621 24.621 3.703 12.343 12.343
2 2.245 9.390 49.415 2.128 7.092 31.713 3.451 11.503 23.847
3 1.577 6.596 56.010 1.892 6.307 38.021 2.802 9.340 33.187
4 1.451 6.066 62.077 1.354 4.512 42.533 2.389 7.962 41.149
5 1.053 4.406 66.482 1.774 5.913 48.446 1.427 4.758 45.907
6 .938 3.921 70.403 1.049 3.495 51.941 1.338 4.461 50.369
7 .901 3.766 74.170 .859 2.862 54.803 1.330 4.434 54.803
8 .766 3.201 77.371            
9 .632 2.643 80.014            
10 .540 2.258 82.272            
11 .510 2.133 84.405            
12 .470 1.967 86.372            
13 .434 1.817 88.188            
14 .388 1.624 89.812            
15 .356 1.488 91.301            
16 .295 1.235 92.536            
17 .282 1.179 93.715            
18 .260 1.088 94.803            
19 .206 .860 95.663            
20 .182 .762 96.425            
21 .159 .663 97.088            
22 .142 .592 97.681            
23 .111 .464 98.145            
24 .086 .358 98.503            
25 .085 .355 98.858            
26 .076 .320 99.177            
27 .061 .255 99.432            
28 .051 .214 99.646            
29 .045 .186 99.833            
30 .040 .167 100.000            
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 7, 2020
Scree Plot Component Number: 30
Eigenvalue: 0.0400 Component Number: 29
Eigenvalue: 0.0446 Component Number: 28
Eigenvalue: 0.0512 Component Number: 27
Eigenvalue: 0.0609 Component Number: 26
Eigenvalue: 0.0765 Component Number: 25
Eigenvalue: 0.0848 Component Number: 24
Eigenvalue: 0.0856 Component Number: 23
Eigenvalue: 0.1110 Component Number: 22
Eigenvalue: 0.1416 Component Number: 21
Eigenvalue: 0.1586 Component Number: 20
Eigenvalue: 0.1822 Component Number: 19
Eigenvalue: 0.2058 Component Number: 18
Eigenvalue: 0.2601 Component Number: 17
Eigenvalue: 0.2819 Component Number: 16
Eigenvalue: 0.2954 Component Number: 15
Eigenvalue: 0.3559 Component Number: 14
Eigenvalue: 0.3883 Component Number: 13
Eigenvalue: 0.4344 Component Number: 12
Eigenvalue: 0.4704 Component Number: 11
Eigenvalue: 0.5099 Component Number: 10
Eigenvalue: 0.5400 Component Number: 9
Eigenvalue: 0.6319 Component Number: 8
Eigenvalue: 0.7655 Component Number: 7
Eigenvalue: 0.9006 Component Number: 6
Eigenvalue: 0.9377 Component Number: 5
Eigenvalue: 1.0535 Component Number: 4
Eigenvalue: 1.4506 Component Number: 3
Eigenvalue: 1.5772 Component Number: 2
Eigenvalue: 2.2454 Component Number: 1
Eigenvalue: 9.5708 Component Number: 29
Eigenvalue: 0.0446 Component Number: 28
Eigenvalue: 0.0512 Component Number: 27
Eigenvalue: 0.0609 Component Number: 26
Eigenvalue: 0.0765 Component Number: 25
Eigenvalue: 0.0848 Component Number: 24
Eigenvalue: 0.0856 Component Number: 23
Eigenvalue: 0.1110 Component Number: 22
Eigenvalue: 0.1416 Component Number: 21
Eigenvalue: 0.1586 Component Number: 20
Eigenvalue: 0.1822 Component Number: 19
Eigenvalue: 0.2058 Component Number: 18
Eigenvalue: 0.2601 Component Number: 17
Eigenvalue: 0.2819 Component Number: 16
Eigenvalue: 0.2954 Component Number: 15
Eigenvalue: 0.3559 Component Number: 14
Eigenvalue: 0.3883 Component Number: 13
Eigenvalue: 0.4344 Component Number: 12
Eigenvalue: 0.4704 Component Number: 11
Eigenvalue: 0.5099 Component Number: 10
Eigenvalue: 0.5400 Component Number: 9
Eigenvalue: 0.6319 Component Number: 8
Eigenvalue: 0.7655 Component Number: 7
Eigenvalue: 0.9006 Component Number: 6
Eigenvalue: 0.9377 Component Number: 5
Eigenvalue: 1.0535 Component Number: 4
Eigenvalue: 1.4506 Component Number: 3
Eigenvalue: 1.5772 Component Number: 2
Eigenvalue: 2.2454 Component Number: 1
Eigenvalue: 9.5708 0 2 4 6 8 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

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Factor Analysis
Factor Analysis - Component Matrix - February 7, 2020
Component MatrixaComponent Matrix, table, 3 levels of column headers and 1 levels of row headers, table with 15 columns and 36 rows
  Raw Rescaled
Component Component
1 2 3 4 5 6 7 1 2 3 4 5 6 7
K1a Lending money to family members -.068 .067 .240 .051 .175 .096 .027 -.138 .135 .483 .103 .353 .193 .054
K1b Lending money to relatives -.044 .075 .213 .068 .188 .103 -.002 -.089 .149 .425 .136 .375 .205 -.003
K1c Lending money to people in your own village -.007 .059 .200 .082 .155 .103 .082 -.014 .122 .409 .167 .317 .210 .168
K1d Lending money to people outside the village .000 .057 .055 .064 .072 .060 .045 .000 .157 .150 .176 .197 .166 .123
K1e Lending money to people from the same mosque/ church -.029 .029 .116 .062 .042 .049 .024 -.080 .079 .318 .170 .115 .135 .066
K2a Lending tools like axes, hoes etc. to family members -.105 .062 .127 .047 .100 .044 .043 -.231 .137 .279 .102 .221 .096 .095
K2b Lending tools like axes, hoes etc. to relatives outside the household -.070 .075 .041 .032 .115 .003 .070 -.164 .175 .097 .076 .269 .007 .163
L2 Participated in cooperative agricultural work .013 .056 .060 .087 .159 .109 .092 .027 .114 .122 .176 .322 .221 .186
L3.d. Participated last 12 months in cooperative work of weeding .009 .021 .030 .049 .082 .106 .085 .023 .056 .080 .131 .217 .280 .226
L3.e. Participated last 12 months in cooperative work of harvesting .002 .054 .018 .055 .110 .080 .082 .004 .134 .045 .138 .276 .199 .205
L3.f. Participated last 12 months in cooperative work of other agriculture work .023 .107 .073 .065 .119 -.023 .045 .065 .308 .210 .186 .343 -.066 .130
L6 Participation in other exchange work than agriculture -.067 .107 .139 .059 .169 .089 .054 -.134 .214 .277 .119 .338 .178 .109
L7 Participated in public works without payment during the last year -.036 -.123 -.080 -.066 -.151 .009 .018 -.090 -.308 -.201 -.166 -.379 .023 .045
M1 Most people can be trusted (1) or you cannot be too careful (0) .163 .156 .030 .050 .087 .000 .075 .327 .313 .060 .099 .174 .000 .150
M2.d. Trust in Traditional Authorities .798 -.487 .273 -.376 -.017 -.012 -.191 .683 -.417 .234 -.321 -.015 -.010 -.164
M2.e. Trust in group village headmen .880 -.446 .297 -.385 .106 .008 -.188 .736 -.373 .249 -.322 .088 .007 -.157
M2.f. Trust in village headmen .921 -.435 .285 -.089 .112 -.084 -.147 .763 -.361 .236 -.074 .092 -.070 -.122
M2.j. Trust in police .855 -.249 -.323 -.049 .560 .416 .321 .668 -.195 -.252 -.038 .438 .325 .251
M2.k. Trust in traders .799 -.148 -.826 .308 .049 .077 -.471 .603 -.112 -.624 .232 .037 .058 -.356
M2.l. Trust in teachers .750 -.343 -.076 .194 -.234 -.112 .373 .685 -.313 -.069 .177 -.214 -.102 .340
M2.m.Trust in school administrators .835 -.319 -.149 .293 -.135 -.160 .338 .712 -.272 -.127 .250 -.115 -.136 .288
M2.n. Trust in religious leaders .695 -.139 .195 .322 -.150 -.260 .189 .627 -.126 .176 .290 -.136 -.234 .170
M3.a. Trust in family members .497 .144 .292 .304 -.076 .135 -.028 .531 .154 .312 .325 -.081 .144 -.030
M3.b. Trust in relatives .653 .310 .330 .620 .092 .065 -.280 .564 .268 .285 .536 .080 .056 -.242
M3.c. Trust in people in own village .798 .287 .084 .151 .079 -.131 -.149 .725 .261 .076 .138 .072 -.119 -.136
M3.d. Trust in people outside the village .680 .464 -.109 -.151 .270 -.494 .107 .607 .414 -.097 -.135 .241 -.441 .095
M3.e. Trust in people of same ethnic group .778 .485 .044 -.286 -.066 .059 -.007 .710 .442 .041 -.261 -.060 .054 -.007
M3.f. Trust in people outside ethnic group .782 .525 -.082 -.232 .035 -.175 -.028 .698 .469 -.074 -.208 .031 -.157 -.025
M3.g. Trust in people from same church/ mosque .692 .161 .137 .031 -.472 .437 -.008 .648 .151 .128 .029 -.442 .409 -.007
M3.h. Trust in people not from same church/ mosque .822 .500 -.162 -.342 -.241 .247 .171 .677 .412 -.133 -.281 -.199 .204 .141
Extraction Method: Principal Component Analysis.
a. 7 components extracted.
Factor Analysis
Factor Analysis - Rotated Component Matrix - February 7, 2020
Rotated Component MatrixaRotated Component Matrix, table, 3 levels of column headers and 1 levels of row headers, table with 15 columns and 36 rows
  Raw Rescaled
Component Component
1 2 3 4 5 6 7 1 2 3 4 5 6 7
K1a Lending money to family members -.031 .309 .044 -.070 .028 -.015 -.077 -.062 .622 .088 -.140 .057 -.029 -.155
K1b Lending money to relatives -.017 .300 .044 -.075 .060 -.017 -.040 -.034 .599 .089 -.150 .119 -.033 -.080
K1c Lending money to people in your own village -.006 .297 .031 .010 .020 .014 -.035 -.013 .609 .064 .021 .041 .028 -.071
K1d Lending money to people outside the village .013 .139 -.027 .009 .021 .016 .016 .036 .380 -.074 .026 .057 .045 .043
K1e Lending money to people from the same mosque/ church -.032 .138 -.002 .001 .035 .018 -.048 -.087 .377 -.006 .004 .095 .050 -.131
K2a Lending tools like axes, hoes etc. to family members -.037 .192 -.041 -.050 -.005 -.028 -.062 -.082 .422 -.090 -.109 -.011 -.062 -.137
K2b Lending tools like axes, hoes etc. to relatives outside the household .019 .145 -.065 -.022 -.033 -.062 -.009 .045 .341 -.153 -.052 -.078 -.145 -.022
L2 Participated in cooperative agricultural work .015 .230 -.018 .024 -.002 .006 .075 .031 .468 -.037 .049 -.003 .011 .152
L3.d. Participated last 12 months in cooperative work of weeding -.008 .148 -.014 .028 -.027 .041 .061 -.022 .392 -.037 .075 -.071 .109 .161
L3.e. Participated last 12 months in cooperative work of harvesting .021 .158 -.037 .016 -.021 .007 .064 .052 .394 -.092 .040 -.051 .018 .160
L3.f. Participated last 12 months in cooperative work of other agriculture work .088 .157 -.028 .016 .039 -.057 -.015 .253 .451 -.081 .047 .111 -.163 -.044
L6 Participation in other exchange work than agriculture .009 .270 -.031 -.060 .006 -.018 -.018 .017 .540 -.062 -.119 .013 -.035 -.035
L7 Participated in public works without payment during the last year -.100 -.167 .003 .030 -.085 .064 -.004 -.252 -.420 .008 .075 -.214 .161 -.011
M1 Most people can be trusted (1) or you cannot be too careful (0) .203 .130 -.006 .076 .046 .021 .037 .406 .260 -.012 .152 .093 .043 .074
M2.d. Trust in Traditional Authorities .181 -.215 .982 .237 .049 .151 .048 .155 -.184 .841 .203 .042 .129 .041
M2.e. Trust in group village headmen .267 -.121 1.043 .229 .060 .124 .106 .224 -.101 .872 .191 .050 .104 .089
M2.f. Trust in village headmen .245 -.064 .918 .429 .242 .042 .130 .203 -.053 .760 .355 .200 .035 .107
M2.j. Trust in police .349 .275 .512 .409 -.196 .130 .898 .273 .215 .400 .320 -.153 .102 .702
M2.k. Trust in traders .293 -.542 .158 .224 .549 .040 .953 .221 -.409 .119 .169 .414 .030 .720
M2.l. Trust in teachers .171 -.189 .303 .842 .025 .183 .175 .157 -.173 .277 .769 .023 .167 .160
M2.m.Trust in school administrators .239 -.171 .291 .889 .121 .095 .284 .203 -.146 .248 .758 .103 .081 .242
M2.n. Trust in religious leaders .255 -.021 .288 .726 .296 .052 -.065 .230 -.019 .260 .655 .267 .047 -.058
M3.a. Trust in family members .217 .227 .178 .291 .411 .292 -.025 .232 .243 .190 .311 .439 .312 -.026
M3.b. Trust in relatives .349 .355 .157 .288 .848 .165 .067 .302 .307 .135 .249 .733 .143 .058
M3.c. Trust in people in own village .637 .043 .286 .272 .459 .084 .117 .579 .039 .260 .247 .417 .077 .107
M3.d. Trust in people outside the village .945 -.025 .131 .228 .063 -.264 .058 .844 -.023 .117 .204 .057 -.236 .052
M3.e. Trust in people of same ethnic group .831 -.019 .277 .063 .098 .385 .051 .759 -.017 .253 .058 .089 .351 .047
M3.f. Trust in people outside ethnic group .935 -.094 .198 .102 .140 .142 .087 .835 -.084 .177 .091 .125 .126 .078
M3.g. Trust in people from same church/ mosque .299 -.058 .243 .261 .258 .806 .052 .280 -.055 .228 .244 .242 .754 .049
M3.h. Trust in people not from same church/ mosque .843 -.120 .154 .145 -.074 .637 .193 .695 -.099 .126 .119 -.061 .524 .159
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 7, 2020
Component Transformation MatrixComponent Transformation Matrix, table, 1 levels of column headers and 1 levels of row headers, table with 8 columns and 10 rows
Component 1 2 3 4 5 6 7
1 .570 -.079 .518 .455 .250 .241 .271
2 .695 .242 -.522 -.315 .160 .179 -.171
3 -.100 .526 .418 .017 .162 .107 -.708
4 -.285 .273 -.410 .465 .656 -.084 .150
5 .136 .592 .211 -.208 -.082 -.592 .432
6 -.275 .364 .050 -.260 -.060 .731 .429
7 .083 .320 -.263 .606 -.667 .084 -.056
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
Factor Analysis
Factor Analysis - Component Plot of Factors 1, 2, 3 - February 7, 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: 0.2236
Component 2: -0.1008
Component 3: 0.8721 Component 1: 0.1548
Component 2: -0.1839
Component 3: 0.8406 Component 1: 0.2027
Component 2: -0.0532
Component 3: 0.7602 Component 1: 0.7585
Component 2: -0.0173
Component 3: 0.2525 Component 1: 0.8355
Component 2: -0.0835
Component 3: 0.1766 Component 1: 0.8437
Component 2: -0.0226
Component 3: 0.1168 Component 1: 0.5791
Component 2: 0.0392
Component 3: 0.2601 Component 1: 0.2726
Component 2: 0.2150
Component 3: 0.4005 Component 1: 0.6946
Component 2: -0.0991
Component 3: 0.1265 Component 1: 0.2296
Component 2: -0.0190
Component 3: 0.2599 Component 1: 0.3017
Component 2: 0.3065
Component 3: 0.1355 Component 1: 0.2799
Component 2: -0.0546
Component 3: 0.2275 Component 1: 0.2321
Component 2: 0.2429
Component 3: 0.1898 Component 1: 0.2034
Component 2: -0.1462
Component 3: 0.2480 Component 1: 0.1566
Component 2: -0.1727
Component 3: 0.2770 Component 1: 0.4062
Component 2: 0.2595
Component 3: -0.0124 Component 1: -0.0336
Component 2: 0.5991
Component 3: 0.0887 Component 1: 0.2528
Component 2: 0.4508
Component 3: -0.0806 Component 1: -0.0128
Component 2: 0.6088
Component 3: 0.0644 Component 1: 0.2215
Component 2: -0.4093
Component 3: 0.1191 Component 1: -0.0625
Component 2: 0.6217
Component 3: 0.0877 Component 1: 0.0308
Component 2: 0.4678
Component 3: -0.0366 Component 1: 0.0171
Component 2: 0.5398
Component 3: -0.0624 Component 1: 0.0358
Component 2: 0.3804
Component 3: -0.0739 Component 1: -0.0220
Component 2: 0.3921
Component 3: -0.0372 Component 1: 0.0521
Component 2: 0.3943
Component 3: -0.0916 Component 1: -0.0869
Component 2: 0.3775
Component 3: -0.0059 Component 1: 0.0452
Component 2: 0.3405
Component 3: -0.1525 Component 1: -0.0825
Component 2: 0.4222
Component 3: -0.0900 Component 1: -0.2524
Component 2: -0.4198
Component 3: 0.0075