Comparison of four mathematical models for the calculation of radioimmunoassay data of LH, FSH, and GH.

Weighted linear logit-log regression, point-to-point logit-log interpolation, smoothing spline approximation and the four-parameter logistic function calculated by non-linear regression have been compared. The data for comparison have been obtained from two different pool-sera for each of the LH-, FSH- and GH-RIA and from the basal serum LH values of two populations of children. The Wilcoxon matched pairs signed rank test was used for comparison: For GH there is no significant difference between all methods, for FSH the weighted linear logit-log regression and spline approximation appeared to be equivalent, but for LH no unequivocal assertion can be made. There is no significant difference between the mathematical models for determination of hormone concentration within one assay-run of a population as exemplified for LH. In addition, pool-sera data were subjected to an analysis of variance and the comparison of the results revealed that the different models did not lead to different statements about assay performance. The point-to-point logit-log interpolation is proposed as most simple curvilinear approximation for assays which cannot be linearized by logit-log transformation.