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Updated: Apr 27, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study
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Measurement Error in the AFQT in the NLSY79.

Lynne Steuerle Schofield1

  • 1Department of Mathematics and Statistics Swarthmore College 500 College Avenue Swarthmore, PA 19081 lschofi1@swarthmore.edu 610-328-7896.

Economics Letters
|July 1, 2014
PubMed
Summary

Item response data can improve social science research by addressing measurement errors in human capital proxies. This method enhances the analysis of economic, social, and psychometric studies, utilizing new data from the Armed Forces Qualifying Test.

Area of Science:

  • Social Sciences
  • Economics
  • Psychometrics

Background:

  • Many social science studies aim to predict future outcomes using human capital measures.
  • Proxies for human capital are often measured with error, introducing bias into regression analyses.

Purpose of the Study:

  • To demonstrate how item-level data can mitigate measurement error in human capital proxies.
  • To highlight the utility of newly released item response data from the Armed Forces Qualifying Test (AFQT) in the 1979 National Longitudinal Survey of Youth (NLSY).

Main Methods:

  • Utilizing item response data, which provides detailed information on individual questions or items within a larger test.
  • Applying regression analysis techniques that account for measurement error in predictor variables.
Keywords:
AFQTMeasurement errorNLSY79

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Main Results:

  • Item-level data offers a method to correct for bias caused by measurement error in human capital proxies.
  • The new AFQT item response data from the NLSY provides a valuable resource for implementing these improved analytical methods.

Conclusions:

  • Leveraging item response data is crucial for more accurate social science research.
  • The availability of detailed item-level data significantly enhances the potential for robust economic, social, and psychometric studies.