Performance assessment of coupled tests: the effects of statistical non-independence.

Limited to two-test associations (series and parallel schemes), the effects of statistical non-independence were studied through a mathematical approach and an experimentally-based evaluation. Both procedures were applied to results for total hormones and free fractions in euthyroid and dysthyroid subjects. Assuming independence, the sensitivity of combined tests was found to increase in parallel coupling, and to decrease, symmetrically, in series coupling, depending critically on the degree of between-test correlation and on the value of single test sensitivity (the opposite modifications obviously occur for specificity). A more complicated situation resulted for the predictive value of test associations, where a prediction based on a mathematical model was found not to be generally valid; in this case, calculations using the correct values of conditional probabilities of coupled tests seemingly remain the safest procedure.