Drop the Likelihood Ratio - Herich, L.; Lehmacher, W.; Hellmich, M. (Methods of Information in Medicine, 2015)
Objective: To present a geometric ruler to determine predictive values of binary diagnostic test results from prevalence, sensitivity and specificity without calculation.Methods: On logarithmic scale the relationships between pre-/post-test odds and the likelihood ratio as well as sensitivity, specificity and the likelihood ratio appear as simple linear (additive) equations.Results: Each of these additive equations can be solved geometrically in form of a ruler with three scales. By amalgamation we devise a novel non-electronic tool which omits the intermediate step of likelihood ratio determination.Conclusions: We propose a simple geometric method to aid in interpretation of diagnostic test results for both practical and educational purposes.
Keywords: Bayes’ rule; Caraguel-Vanderstichel nomo-gram; ruler; diagnostic test