In several context ranging from medical to social sciences, rater reliability is assessed in terms of intra (-inter) rater agreement. The extent of rater agreement is commonly characterized by comparing the value of the adopted agreement coefficient against a benchmark scale. This deterministic approach has been widely criticized since it neglects the influence of experimental conditions on the estimated agreement coefficient. In order to overcome this criticism, in this paper a statistical procedure for benchmarking is presented. The proposed procedure is based on non parametric bootstrap confidence intervals. The statistical properties of the proposed procedure have been studied via a Monte Carlo simulation.
Characterizing the extent of rater agreement via a non-parametric benchmarking procedure / Vanacore, Amalia; Pellegrino, MARIA SOLE. - (2017), pp. 999-1004. (Intervento presentato al convegno SIS 2017. Statistics and Data Science: new challenges, new generations. tenutosi a Firenze nel 28-30 June 2017).
Characterizing the extent of rater agreement via a non-parametric benchmarking procedure
VANACORE, AMALIA
Methodology
;PELLEGRINO, MARIA SOLE
2017
Abstract
In several context ranging from medical to social sciences, rater reliability is assessed in terms of intra (-inter) rater agreement. The extent of rater agreement is commonly characterized by comparing the value of the adopted agreement coefficient against a benchmark scale. This deterministic approach has been widely criticized since it neglects the influence of experimental conditions on the estimated agreement coefficient. In order to overcome this criticism, in this paper a statistical procedure for benchmarking is presented. The proposed procedure is based on non parametric bootstrap confidence intervals. The statistical properties of the proposed procedure have been studied via a Monte Carlo simulation.File | Dimensione | Formato | |
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