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multivariate location R and scatter R are defined by minimizing the determinant of the covariance matrix and generalized distances, D T R 2 1 ( ) ( ) x x R R , are calculated. The distances follow a n 2 distribution (where n is the multivariate dimension) and define corresponding p-values. Outliers are defined as centres with p-values below a pre-defined threshold (e.g. p<0.05). This method can be used for univariate and multivariate KRIs. Furthermore, p-values can be combined across KRIs to form a single score. We provide empirical examples and graphical displays of univariate and multivariate KRI analyses undertaken using this robust MCD distance approach based on a large-scale multicentre cardiovascular trial. Conclusion Robust MCD distances offer a flexible approach for analysing both univariate and multivariate KRIs and can be implemented in standard statistical software.

Central statistical monitoring in multicentre clinical trials: developing statistical approaches for analysing key risk indicators