Abstract: A kit and test panel utilizing a multivariate diagnostic method based on optimizing diagnostic likelihood ratios through the effective use of multiple diagnostic tests is disclosed. The Neyman-Pearson Lemma provides a mathematical basis to produce optimal diagnostic results.

Abstract: A kit and test panel utilizing a multivariate diagnostic method based on optimizing diagnostic likelihood ratios through the effective use of multiple diagnostic tests is disclosed. The Neyman-Pearson Lemma provides a mathematical basis to produce optimal diagnostic results.

Abstract: A multivariate diagnostic method based on optimizing diagnostic likelihood ratios through the effective use of multiple diagnostic tests is disclosed. The Neyman-Pearson Lemma provides a mathematical basis to produce optimal diagnostic results.

Abstract: Methods for constructing multivariate predictive models for diagnosing diseases for which test methods are individually inadequate, including: (a) performing laboratory tests on a statistically significant test population of individuals; (b) generating a score function from a linear combination of test panel results; (c) performing a receiver operating characteristic (ROC) regression or alternative regression technique of the score function using those tests and ? coefficients calculated simultaneously to maximize the area under the curve (AUC) of the function and chosen simultaneously to generate the largest area below that portion of the ROC curve for the (1?t0) quantile of individuals without disease, where t0 represents the maximum acceptable false-positive rate; (d) calculating individual pre-test disease odds; generating a diagnostic likelihood ratio of disease by determining the frequency of each individual's test score in the diseased population relative to the control population; and multiplying p