Abstract Checking dependence structure between variables is important when modeling multivariate data. In this paper, we investigate copulas, functions that provide a flexible methodology for modeling multivariate dependence. In particular, copulas are useful in describing the dependence structure of extreme values in the tails. Gauss, Student t- and Cauchy copulas are considered, among others. We also investigate a method for the choice of copulas. Based on the chosen copula, we demonstrate a simple graphical method with data from a study on multiple myeloma, particularly for analysis of the tail dependence.