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Table 5 Principal components (PCs) or principal factors (PFs) extracted by principal components analysis (PCA) and principal axis factoring (PAF), showing component or factor loadings.

From: Comparison of two approaches for measuring household wealth via an asset-based index in rural and peri-urban settings of Hunan province, China

Variable
(% variance accounted for)
Rural (Wuyi) Peri-urban (Laogang)
  PC 1, PF 1
(24.3%)
PC 2, PF 2
(11.0%)
PC 3, PF 3
(9.4%)
PC 4, PF 4
(8.9%)
PC 1, PF 1
(27.8%)
PC 2, PF 2
(16.5%)
PC 3, PF 3
(12.7%)
2 Own land    - 0.421, n.a. 0.564, 0.436   0.574, -0.408  
3 Own animals    - 0.469, n.a. 0.493, n.a. n.a. n.a. n.a.
4 Gas rice cooker 0.638, 0.573     n.a. n.a. n.a.
5 Microwave 0.464, 0.388     n.a. n.a. n.a.
8 VCR 0.465, 0.405 0.444, n.a.    0.702, 0.613   
9 Satellite dish 0.527, 0.483     n.a. n.a. n.a.
10 Phone line n.a. n.a. n.a. n.a.   -0.736, 0.527  
11 Mobile phone 0.611, 0.553     0.668, 0.585   
13 Motorbike 0.595, 0.525     n.a. n.a. n.a.
15 Air conditioner n.a. n.a. n.a. n.a. 0.585, 0.500   
16 Fridge 0.444, 0.373     0.661, 0.614   
17 Washing machine 0.580, 0.533 0.430, n.a.    0.734, 0.668   
21 Boat     0.669, 0.429    
27 Weak brick roof - 0.564,-0.554     n.a. n.a. n.a.
28 Strong brick roof n.a. n.a. n.a. n.a.   0.827, 0.849  
31 Porcelain floor 0.605, 0.601 n.a., -0.482    0.650, 0.647   n.a., -0.500
35 Flushable toilet 0.694, 0.676     0.561, 0.512   
36 Medicines at home n.a. n.a. n.a. n.a.    0.677, 0.433
38 Over-crowding    0.678, 0.453   n.a. n.a. n.a.
  1. Values shown are for rural (Wuyi village) (left) and peri-urban (Laogang village) (right) settings, Hunan province, China*
  2. n.a, not applicable; 1 Factor loadings reported only if they exceed the cut-off eigenvector of |0.3|;* Rotation method: no rotation used to maximize the squared loadings of the columns.
  3. NB Indices were created using only the first component or factor. Remaining components or factors are shown for clarification purposes. Where variables loaded on more than one component or factor, the one selected is shown in bold. This was done based on the co-efficient α score.