Complexity and categorical analysis may improve the interpretation of agreement studies using continuous variables

• Type: Article in International Scientific Journal
• Date: 2011

Authors

Cristina Costa Santos (Author) FMUP; João Bernardes (Author) FMUP; Luis Antunes (Author) FCUP; Diogo Ayres de Campos (Author) FMUP

Journal

Title: Journal of Evaluation in Clinical Practice

Vol. 17 No. 3

Pages: 511-514

ISSN: 1356-1294

Publisher: Wiley-Blackwell

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 5 Citations

Scientific classification

FOS: Medical and Health sciences > Health sciences

Other information

Authenticus ID: P-002-R7B

DOI: 10.1111/j.1365-2753.2011.01668.x

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4