Log-linear and logistic modeling of dependence among diagnostic tests

We developed log-linear and logistic-modeling approaches to investigate dep endence among diagnostic tests. To illustrate the approaches, we used publi shed data for swine toxoplasmosis, bovine paratuberculosis, and swine bruce llosis, These diseases were selected because each animal's true disease sta tus was known, at least five tests were used, and the serologic tests had b een previously shown to have moderate-to-high pairwise dependence in test s ensitivities (and sometimes in test specificities). Log-linear and logistic modeling yielded similar results for swine toxoplasmosis and swine brucell osis, However, logistic modeling could not be used to investigate test depe ndence for bovine paratuberculosis because of quasi-separation in the data attributable to two fecal-based tests having specificities of 100%. Finding s from our modeling indicated that 3 (modified agglutination, enzyme-linked immunosorbent assay (ELISA), latex agglutination) of 5 serologic tests for toxoplasmosis and 2 (rivanol and particle concentration fluorescence immun oassay) of 6 serologic tests for brucellosis were adequate for diagnosis. F or bovine paratuberculosis, both fecal-based tests (Herrold's egg-yolk cult ure and radiometric culture) and 1 (ELISA) of 3 serologic tests were necess ary in serial and parallel testing schemes. (C) 2000 Elsevier Science B.V. All rights reserved.