A robust likelihood approach to inference about the kappa coefficient for correlated binary data.

We construct a legitimate likelihood function for the agreement kappa coefficient for correlated data without specifically modelling all levels of correlation. This makes available the likelihood ratio test, the score test and other tools without the knowledge of the underlying distributions. This parametric robust likelihood approach applies to general clustered data scenarios. We provide simulations and real data analysis to demonstrate the advantage of the robust procedure.