A comparison of Cohen's Kappa and Gwet's AC1 when calculating inter-rater reliability coefficients: A study conducted with personality disorder samples

Abstract

Background: Rater agreement is important in clinical research, and Cohen's Kappa is a widely used method for assessing inter-rater reliability; however, there are well documented statistical problems associated with the measure. In order to assess its utility, we evaluated it against Gwet's AC1 and compared the results. Methods. This study was carried out across 67 patients (56% males) aged 18 to 67, with a mean SD of 44.13 ± 12.68 years. Nine raters (7 psychiatrists, a psychiatry resident and a social worker) participated as interviewers, either for the first or the second interviews, which were held 4 to 6 weeks apart. The interviews were held in order to establish a personality disorder (PD) diagnosis using DSM-IV criteria. Cohen's Kappa and Gwet's AC1 were used and the level of agreement between raters was assessed in terms of a simple categorical diagnosis (i.e., the presence or absence of a disorder). Data were also compared with a previous analysis in order to evaluate the effects of trait prevalence. Results: Gwet's AC1 was shown to have higher inter-rater reliability coefficients for all the PD criteria, ranging from.752 to 1.000, whereas Cohen's Kappa ranged from 0 to 1.00. Cohen's Kappa values were high and close to the percentage of agreement when the prevalence was high, whereas Gwet's AC1 values appeared not to change much with a change in prevalence, but remained close to the percentage of agreement. For example a Schizoid sample revealed a mean Cohen's Kappa of.726 and a Gwet's AC1of.853, which fell within the different level of agreement according to criteria developed by Landis and Koch, and Altman and Fleiss. Conclusions: Based on the different formulae used to calculate the level of chance-corrected agreement, Gwet's AC1 was shown to provide a more stable inter-rater reliability coefficient than Cohen's Kappa. It was also found to be less affected by prevalence and marginal probability than that of Cohen's Kappa, and therefore should be considered for use with inter-rater reliability analysis. © 2013 Wongpakaran et al.; licensee BioMed Central Ltd.