Statistical inference for serial dilution assay data

Serial dilution assays are widely employed for estimating substance concent rations and minimum inhibitory concentrations. The Poisson-Bernoulli model for such assays is appropriate for count data but not for continuous measur ements that are encountered in applications involving substance concentrati ons. This paper presents practical inference methods based on a log-normal model and illustrates these methods using a case application involving bact erial toxins.