An alternative to evaluate disagreement between two measures via simple linear regression model without intercept

An alternative to evaluate disagreement between two measures via simple linear regression model without intercept

Authors

  • Maria Clara Vieira Borba Departamento de Estatística Universidade de Brasília (UnB)
  • Eduardo Yoshio Nakano Departamento de Estatística Universidade de Brasília (UnB)

DOI:

https://doi.org/10.5433/1679-0375.2016v37n2p41

Keywords:

Concordance, Disagreement, Test-retest, Reliability

Abstract

This paper proposes a statistical method to assess the disagreement between two normally distributed measures. This method consists to test the coefficient of a simple linear regression model without intercept. Artificial dataset from literature and simulated data were used to illustrate this method and compare it to other methods that are wrongly used (such as the paired t-test or the Pearson correlation coefficient). It is noteworthy that, whereas Kendall’s coefficient of concordance and the Intraclass correlation coefficient assess agreement between two quantitative measurements, this new method is an alternative to test the disagreement between these two measurements. This work also presents a computational implementation of the method in the free software R. Finally, this work showed that the proposed method fulfilled its role, even when other procedures (wrongly used) have failed.

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Published

2016-08-16

How to Cite

Borba, M. C. V., & Nakano, E. Y. (2016). An alternative to evaluate disagreement between two measures via simple linear regression model without intercept. Semina: Ciências Exatas E Tecnológicas, 37(2), 41–50. https://doi.org/10.5433/1679-0375.2016v37n2p41

Issue

Section

Original Article
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