Data-reduction methods for immunoradiometric assays of thyrotropin compared

M. C. Haven, P. J. Orsulak, L. L. Arnold, G. Crowley

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1207-1210
Number of pages4
JournalClinical Chemistry
Volume33
Issue number7
StatePublished - Dec 1 1987

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Biochemistry, medical

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    Haven, M. C., Orsulak, P. J., Arnold, L. L., & Crowley, G. (1987). Data-reduction methods for immunoradiometric assays of thyrotropin compared. Clinical Chemistry, 33(7), 1207-1210.