The risk of misclassifying subjects within principal component based asset index

Details

• Alternative Title:
  Emerg Themes Epidemiol
• Personal Author:
  Sharker, MA Yushuf ; Nasser, Mohammed ; Abedin, Jaynal ; Arnold, Benjamin F ; Luby, Stephen P
• Description:
  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.
• Subjects:
  Analytic Perspective Asset Index Principal Component Analysis Socio-economic Status Wealth Index
• Source:
  Emerg Themes Epidemiol. 2014; 11:6.
• Document Type:
  Journal Article
• Volume:
  11
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:956c0e94386e81dfd6c1c519b3c4ecc95ef503b1ce6a310aa0a8678c604fc8f2
• Download URL:
  https://stacks.cdc.gov/view/cdc/24006/cdc_24006_DS1.pdf
• File Type:
  [PDF - 622.22 KB ]