ABSTRACT
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Immunoassays have long been recognized as inexpensive, rapid, and sensitive analytical methods.
Yalow and Berson’s [1] original work using radiochemical tracers sparked activity in developing
assays for medically important compounds. Limitations imposed on the spread of the technology by
dependence on radioactive materials were removed by Engvall and Perlmann’s substitution of
enzyme-based signal generators [2]. Indeed, the recent thirty year anniversary of the latter’s
work recognized the world wide application of the technology to the analysis of biomedical and
environmental analytes of interest. As new analytical needs were met, researchers were often
creative with the means by which the methods and their results were mathematically described.
This has resulted in multiple approaches to modeling immunoassay data. One need only make a
cursory review of the literature to realize that the calculations and manner of processing data are as
varied as the researchers themselves. Although each approach may be valid for a given circum-
stance, this complexity makes it difficult for the novice to appreciate the pitfalls associated with
some models. Moreover, varied criteria for evaluation of data can be misleading.
