In clinical trials in asthma, airway reactivity is commonly assessed by performing a methacholine challenge. Airway reactivity is thought to vary in proportion to asthma severity, and methacholine causes the airways of asthma subjects to constrict, thus lowering forced expiratory volume in 1 second (FEV(1)). A dose-response curve is obtained for each subject who meets standardized eligibility requirements to proceed with a methacholine challenge. When data from a methacholine challenge are used as an outcome variable in analysis, a univariate measure called the PC(20), the concentration of methacholine needed to produce a 20% fall in FEV(1) from baseline, is typically used to summarize the dose-response curve. Questions that arise regarding data generated from the methacholine challenge include: how to express data that do not yield a PC(20) value; whether PC(20) actually represents the best way to capture airway activity as expressed in a methacholine challenge; and whether the baseline FEV(1) is defined appropriately in calculation of PC(20). The impact of these issues on the statistical analysis of methacholine challenge data is described in this article. Some adjustments to the usual estimates of PC(20) and parametric modeling of the entire dose-response curve are proposed as alternatives that address some of the shortcomings of PC(20).