The predictive value of clinical laboratory test results

Bayes' formula is being used with increasing frequency to calculate predictive values for positive and negative clinical laboratory test results. Because of its nonlinear form, however, it is difficult to visualize how changes in the test characteristics or disease prevalence will effect predictive values. This paper shows that Bayes' formula is transformed to a linear function through the use of odds, rather than probabilities, thus facilitating conceptualization, understanding, and memory.