Several algorithms have been developed to calculate multivariate risk of CVD based on characteristics associated with the disease. Framingham Heart Study data were used to develop the original algorithms, along with later models, using different mathematical forms, outcomes, and characteristics. Researchers then began to investigate the issue of generalizability, whether these risk estimates could be applied to new populations. For these algorithms to have general application, they must be able to rank risk correctly. And, when Framingham models were compared to new models developed for other studies, resulting orderings of risk were, in fact, similar.