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Using repeated measures to correct correlated measurement errors through orthogonal decomposition

Author

Listed:
  • Chang Yu
  • Sanguo Zhang
  • Christine Friedenreich
  • Charles E. Matthews

Abstract

In a physical activity (PA) study, the 7-day PA log viewed as an alloyed gold standard was used to correct the measurement error in the physical activity questionnaire. Due to correlations between the errors in the two measurements, the usual regression calibration (RC) may result in a biased estimate of the calibration factor. We propose a method for removing the correlation through orthogonal decomposition of the errors, and then the usual RC can be applied. Simulation studies show that our method can effectively correct the bias.

Suggested Citation

  • Chang Yu & Sanguo Zhang & Christine Friedenreich & Charles E. Matthews, 2017. "Using repeated measures to correct correlated measurement errors through orthogonal decomposition," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(23), pages 11604-11611, December.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:23:p:11604-11611
    DOI: 10.1080/03610926.2016.1275693
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