Performance of various mathematical methods for computer-aided processing of radioimmunoassay results.
Interpolation and regression methods are available for computer aided determination of radioimmunological end results. We compared the performance of 6 algorithms (weighted and unweighted linear logit log regression; quadratic logit log regression, smoothing spline interpolation with a large and small smoothing factor, respectively, and polygonal interpolation and the manual curve fitting on the basis of three radioimmunoassays with different reference curve characteristics (digoxin, estriol, human chorionic somatomammotrophin (HCS)). Great store was set by the accuracy of the approximation at the intermediate points on the curve, i.e. those points that lie midway between two standard concentrations. These concentrations were obtained by weighing and inserted as unknown samples. In the case of digoxin and estriol the polygonal interpolation provided the best results, while the weighted logit log regression proved superior in the case of HCS.
D003201:Computers; D004077:Digoxin / Q000032:analysis; D004964:Estriol / Q000032:analysis; D006801:Humans; D008433:Mathematics; D008962:Models, Theoretical; D010928:Placental Lactogen / Q000032:analysis; D011863:Radioimmunoassay / Q000379:methods*
D004077:Digoxin; D010928:Placental Lactogen; D004964:Estriol