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Ordinary least products regression is a simple and powerful statistical tool to identify systematic disagreement between two measures: fixed and proportional bias assessment

Author

Listed:
  • Marcus Vinicius Nascimento Ferreira

    (1YCARE (Youth/Child cArdiovascular Risk and Environmental) Research Group, Faculdade de Medicina, Un)

  • Augusto César Ferreira De Moraes
  • Tara Rendo-Urteaga1
  • Silvia Bel-Serrat
  • Francisco Leonardo Torres-Leal
  • Luis A. Moreno
  • Heráclito Barbosa Carvalho

Abstract

Background: We aimed to provide a statistical procedure to assess systematic disagreement between two measures assuming that measurements made by either method are attended by random error. Methods: We applied Bland-Altman analysis (baplot) and ordinary least products (OLP) regression (manually) in three simulated pairs of samples (N=100). In OLP, values of y and x are used in the major axis regression analysis, but then intercept and slope are back-transformed by dividing them by (). Fixed bias was defined if 95% confidence interval (CI) of the intercept does not include 0. Proportional bias was defined if 95%CI of the slope does not include 1. Results: Using baplot, we found no fixed (bias=3.4 minutes/day; 95%CI=-10.4-17.2) and no proportional (r=-0.2; p=0.09) bias for physical activity (PA); and, fixed (bias=-5.3 hour/day, 95%CI=-5.4--5.2; bias=4.5 hour/day; 95%CI=4.3- 4.7) and proportional (r=-0.9; p

Suggested Citation

  • Marcus Vinicius Nascimento Ferreira & Augusto César Ferreira De Moraes & Tara Rendo-Urteaga1 & Silvia Bel-Serrat & Francisco Leonardo Torres-Leal & Luis A. Moreno & Heráclito Barbosa Carvalho, 2018. "Ordinary least products regression is a simple and powerful statistical tool to identify systematic disagreement between two measures: fixed and proportional bias assessment," 2018 Stata Conference 34, Stata Users Group.
    • Handle: RePEc:boc:scon18:34
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