An improved processing of radioimmunoassay data by means of a desk-top calculator (1) comparison of regression procedures applied to selected kinds of radioimmunoassay

Abstract

By means of a programmable desk-top calculator, goodness-of-fit of 3 regression models, four-parameter logistic, quadratic logit-log and linear logit-log models, were evaluated by analysis of variance ( F test) for data of 6 kinds of radioimmunoassays (RIA); thyroid stimulating hormone (TSH), luteinizing hormone (LH), follicle-stimulating hormone (FSH), insulin (IRI), cortisol, triiodothyronine (T 3). Scatchard plot analyses were made with the representative data of these RIAs in order to find the best choice of regression model in relation to the characteristics of antigen-antibody reaction. The analysis of goodness-of-fit of the regression models by means of an F test disclosed the relation between the choice of regression models and the kinds of RIA, which could be grouped into 3 types: (1) almost identical degree of fit with any of 3 regression models (FSH and T 3), (2) more or less equal degree of satisfactory fit with the logistic and quadratic logit-log models (TSH and cortisol), (3) best degree of fit with the quadratic logit-log model among 3 (LH and IRI). The analysis of data with Scatchard plot discriminated 3 general types of curves; (1) linear (FSH) and T 3), (2) linear with tail (TSH and cortisol) and (3) hyperbola (LH and IRI). From these findings, the following tentative conclusions were reached: RIA with linear pattern on Scatchard plot can be satisfactorily regressed with either of 3 models, RIA with linear with tail pattern regressed with either the logistic or quadratic logit-log model, and RIA with hyperbolic pattern regressed best with the quadratic logit-log model.