title: Complexity and categorical analysis may improve the interpretation of agreement studies using continuous variables.
abstract: BACKGROUND
  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.
  
  
  OBJECTIVE
  We aim to improve the interpretation of agreement studies using continues variables.
  
  
  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.
authors.affiliation: Department of Biostatistics and Medical Informatics, Faculty of Medicine, University of Porto, Porto, Portugal. csantos@med.up.pt
authors.forename: Cristina
authors.initials: C
authors.lastname: Costa-Santos
authors.forename: João
authors.initials: J
authors.lastname: Bernardes
authors.forename: Luís
authors.initials: L
authors.lastname: Antunes
authors.forename: Diogo
authors.initials: D
authors.lastname: Ayres-de-Campos
mesh_terms: D035843:Biomedical Research / Q000379:methods*; D003627:Data Interpretation, Statistical; D003657:Decision Making; D005260:Female; D006340:Heart Rate, Fetal; D006801:Humans; D015588:Observer Variation; D011247:Pregnancy; D011256:Pregnancy Outcome; D015203:Reproducibility of Results; D035501:Uncertainty