Many treatment studies compare a treatment group with a waiting list control group, for example to adjust for spontaneous remissions. Unfortunately, many more participants drop out from the waiting list control group than from the treatment group.
One reason for participants dropping out from the waiting list group might be that the condition for which they had been seeking treatment has disappeared and that they no longer are interested in participating in a treatment they no longer need. Unfortunately these dropouts make the waiting list group "more sick" on average than it would have been, thus confounding results. Other dropouts may differ in personality or other relevant factors from the remaining participants, thus reducing the quality of the random group assignment.
How do you deal with these dropouts in data preparation and analysis?
I often see that participants are matched according to age, gender and socioeconomic status. But this does not compensate for spontaneous remission dropout or other factors of which we might be unaware. Are there other, maybe better methods?
I have no idea what the appropriate tags might be. Please edit this question, if you know. Thank you.