Emerging Themes in Epidemiology | |
The risk of misclassifying subjects within principal component based asset index | |
Stephen P Luby2  Benjamin F Arnold3  Jaynal Abedin4  Mohammed Nasser1  MA Yushuf Sharker4  | |
[1] Department of Statistics, University of Rajshahi, 6205 Rajshahi, Bangladesh;Global Disease Detection Branch, Division of Global Health Protection, Center for Global Health, Centers for Disease Control and Prevention, Georgia, USA;School of Public Health, University of California, Berkeley, USA;icddr,b, 68 Shahid Tajuddin Ahamed Sarani, Mohakhali, 1212 Dhaka, Bangladesh | |
关键词: Wealth index; Asset index; Socio-economic status; Principal component analysis; | |
Others : 800813 DOI : 10.1186/1742-7622-11-6 |
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received in 2013-12-20, accepted in 2014-06-10, 发布年份 2014 | |
【 摘 要 】
The asset index is often used as a measure of socioeconomic status in empirical research as an explanatory variable or to control confounding. Principal component analysis (PCA) is frequently used to create the asset index. We conducted a simulation study to explore how accurately the principal component based asset index reflects the study subjects’ actual poverty level, when the actual poverty level is generated by a simple factor analytic model. In the simulation study using the PC-based asset index, only 1% to 4% of subjects preserved their real position in a quintile scale of assets; between 44% to 82% of subjects were misclassified into the wrong asset quintile. If the PC-based asset index explained less than 30% of the total variance in the component variables, then we consistently observed more than 50% misclassification across quintiles of the index. The frequency of misclassification suggests that the PC-based asset index may not provide a valid measure of poverty level and should be used cautiously as a measure of socioeconomic status.
【 授权许可】
2014 Sharker et al.; licensee BioMed Central Ltd.
【 预 览 】
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20140708000249525.pdf | 622KB | download | |
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Figure 1. | 47KB | Image | download |
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