OBJECTIVES: In research on the effectiveness of chemotherapy, a key measure of treatment delivery is average relative dose intensity (ARDI), which summarizes delivered dosage per unit of time, relative to an accepted standard. In clinical trials, where dosages and timing are strictly controlled, the calculation and use of ARDI are well-understood. In actual practice, however, naturally-occurring events complicate the computation and interpretation of this statistic: dosage levels can be reduced, treatment cycles can be delayed or eliminated entirely, and the prescribed regimen can differ materially from the published standard. In recent naturalistic research studies and clinical performance improvement programs, various alternative methods of calculating ARDI have been presented, and have been given a variety of interpretations. The objectives of this paper are to critically evaluate the alternatives and present a set of statistics with known psychometric properties and unambiguous interpretation. METHODS: Data from several cancer registries and retrospective studies were mined to identify and categorize the various naturally-occurring scenarios impacting ARDI. RESULTS: Three statistics were derived from these samples, which discriminate among three key ARDI aspects, labeled "planned ARDI", "delivered ARDI" and "% Optimal Dose". They measure, respectively, the physician's prescribed dose intensity, the actual delivered dose intensity, and the total delivered dose independent of time, all relative to the associated standard. Several visualization and analysis techniques are also presented that employ these measures to determine the relative contribution of the various fundamental causes of suboptimal dose administration. These causes include cycle delay, dose reduction, treatment attenuation and planned deviation. CONCLUSIONS: The methods presented provide those engaged in naturalistic research and clinical performance improvement with a validated set of statistics and a concise, unambiguous terminology to measure and interpret the complex treatments involved in the study of chemotherapy effectiveness.