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

Marcus Vinicius Nascimento Ferreira (), Augusto César Ferreira De Moraes, Tara Rendo-Urteaga1, Silvia Bel-Serrat, Francisco Leonardo Torres-Leal, Luis A. Moreno and Heráclito Barbosa Carvalho
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Marcus Vinicius Nascimento Ferreira: 1YCARE (Youth/Child cArdiovascular Risk and Environmental) Research Group, Faculdade de Medicina, Un

2018 Stata Conference from Stata Users Group

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

Date: 2018-08-02
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Persistent link: https://EconPapers.repec.org/RePEc:boc:scon18:34

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