Intention to treat analysis in clinical trials when there are missing data

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 baseline, 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 complete 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, they sometimes have second thoughts about continuing with the research (perhaps because of adverse effects); they may get tired of the necessity to complete a questionnaire a number of times or to come into the clinic on a weekly basis in order to have blood drawn; they may move out of town; or they may, of course, die before the study ends. Whenever follow up data are incomplete, the researcher faces some major problems. Firstly, because fewer subjects have complete data than was originally planned for, …