Intention

to treat analysis in clinical trials when there are missing data The problem If you open any book about research design or statistics, you will see examples of studies in which 40 or 50 people are randomly assigned to a treatment and a control condition, tested at base› line, and then retested every week for the next 2 months. These texts then extol the virtues of being able to look at changes over time, and how the groups can be compared with regard to the pattern of change. Buried in a footnote (if it’s mentioned at all) is a caveat that, in order to perform the analysis, we need com› plete data on all subjects. If even 1 data point is missing for a person, that subject must be dropped from consideration. Unfortunately, trial participants rarely read our textbooks, and do not know the importance of complete data. Consequently