  The statistical measurement of agreement is important in a number of fields,
e.g., content analysis, education, computational linguistics, biomedical
imaging. We propose Sklar's Omega, a Gaussian copula-based framework for
measuring intra-coder, inter-coder, and inter-method agreement as well as
agreement relative to a gold standard. We demonstrate the efficacy and
advantages of our approach by applying it to both simulated and experimentally
observed datasets, including data from two medical imaging studies. Application
of our proposed methodology is supported by our open-source R package,
sklarsomega, which is available for download from the Comprehensive R Archive
Network.
