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In an attempt to optimize curve fitting for immunoradiometric assays, we investigated eight data-reduction methods with two commercially available assays of thyrotropin. In four of these methods linear data-reduction models are used: logit-log programs of Iso-Data, Micromedic, and Hewlitt-Packard, and probit-log of Hewlitt-Packard. The other four were nonlinear data-reduction models: Iso-Data's "French curve" (modified spline), four-parameter logistic function, and point-to-point methods, as well as a nonlinear least squares method. In using the eight data-reduction methods on data from analyses of 78 patients' samples, we found clinically relevant differences between models. In fact, differences found by changing data-reduction models were greater than the difference between the two commercial kits.
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