The risk of misclassifying subjects within principal component based asset index

Emerging Themes in Epidemiology

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

 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.

【 图 表 】

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