Standardization in the choice of quality of life (QOL) instruments and their application in randomised clinical trials have been advocated and generally accepted. However, there is now an urgent need to address the problems relating to the analysis and presentation of the data thus generated. There are intrinsic difficulties associated with QOL data, namely its multidimensional nature, attrition and missing data, and there is no consensus as to how these problems should be dealt with. This paper therefore considers these problems using interim data from a large Medical Research Council randomised trial in patients with small cell lung cancer and a poor prognosis, in which attrition and compliance are major concerns. Three possible approaches to the analysis of these data, which use different subsets of patients, are examined in detail. The strengths and weaknesses of these three methods are discussed, and examples of their use in the literature are given and compared with other reported approaches. The need for a standard definition of compliance is also emphasised, and a method of presentation suggested. The best current advice is that QOL data should be analysed in a number of different ways, and conclusions reached only when consistency is seen.