Probit regression analysis is frequently used to study the relation between the concentration of an analyte in a sample and the probability that the assay used yields a positive test result. For these analyses only the qualitative classification ‘positive’ or ‘negative’ is used, whereas, particularly in the case where the assay is quantitative in nature, the results contain more information. In the current paper, we propose an alternative method, in which the negative test results are treated as being (left) censored. As such, more efficient use is made of the information in the data. The procedures are illustrated using two generations of NucliSens assays (BioMérieux), which are designed to quantify the viral load of HIV-1 in blood samples. Computer simulations are used to illustrate some properties of the estimated parameters. Copyright © 2003 John Wiley & Sons, Ltd.
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