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Estimates of analyte concentrations, obtained by immunoassay, have error distributions which are generally underestimated. Better estimates, which take into account the distribution of the response metameter of the calibration curve and uncertainties associated with the location of the fitted curve, have been obtained by computer simulation using practical immunoassay data. The increased use of curve-fitting software in automated immunoassay equipment has prompted the investigation of reported analyte concentration distributions for three commonly used functions, namely the logit-log, the 4-parameter logistic and the four-parameter Amersham models. The stimulation model is of potential value for a variety of situations.
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