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Complexity and categorical analysis may improve the interpretation of agreement studies using continuous variables
Author(s) -
CostaSantos Cristina,
Bernardes João,
Antunes Luís,
AyresdeCampos Diogo
Publication year - 2011
Publication title -
journal of evaluation in clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.737
H-Index - 73
eISSN - 1365-2753
pISSN - 1356-1294
DOI - 10.1111/j.1365-2753.2011.01668.x
Subject(s) - categorical variable , intraclass correlation , agreement , interpretation (philosophy) , continuous variable , categorization , statistics , mathematics , econometrics , computer science , medicine , artificial intelligence , psychometrics , philosophy , linguistics , programming language
Rationale Complex clinical scenarios involving a high degree of uncertainty frequently lead to a poor agreement over diagnosis and management. However, inconsistent results can be found with the most widely used measures of agreement for continuous variables – the limits of agreement and the intraclass correlation coefficient. Aims and objectives We aim to improve the interpretation of agreement studies using continues variables. Methods and results Evaluation of agreement may be improved by complexity analysis and by categorization of variables, followed by the use of the proportions of agreement. Conclusions The average never characterizes a complex phenomenon and the methods used to access agreement in continuous variables are based on the mean. For future agreement studies, involving complex continuous variables, we recommend a complexity and categorical analysis.