Methods are presented for assessing and comparing the results of k = 2 independent samples of measured agreement or concordance, where in each sample a given member of a pair of observations is classified according to the presence or absence of a binary trait.
Examples include the assessment of interobserver agreement across different groups of patients in a clinical study, investigations of sibling concordance across different genetic groups, and meta-analyses of observer agreement across different studies.
The methodology described is based on application of goodness-of-fit theory to testing hypotheses concerning kappa statistics.
Partitioning methods allow a variety of hypotheses to be tested, including an assessment of the degree of agreement within each sample, a testing procedure based on the pooled data, and a test of heterogeneity that may be used to assess the validity of pooling across samples.
Three examples are given.
Mots-clés Pascal : Analyse statistique, Modèle mathématique, Métaanalyse, Comparaison interindividuelle, Epidémiologie, Méthodologie, Homme
Mots-clés Pascal anglais : Statistical analysis, Mathematical model, Metaanalysis, Interindividual comparison, Epidemiology, Methodology, Human
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 97-0465509
Code Inist : 002B30A01A1. Création : 03/02/1998.