Measurements made on human subjects rarely give exactly the same results from one occasion to the next. Even in adults our height varies a little during the course of the day. If one measures blood sugar levels of an individual on one particular day and then again the following day, under exactly the same conditions, greater variation in this than that of height would be expected. Hence were such a subject to receive an intervention (perhaps to lower the blood sugar levels) before the next measure then any lowering observed could not necessarily be ascribed to the intervention itself. The levels of inherent variability may be very high so that, perhaps in the circumstances where a subject has an illness, the oscillations in these may disguise, at least in the early stages of treatment, the beneficial effect of the treatment given to improve the condition.
With such variability it follows that, in any comparison made in a biomedical context, differences between subjects or groups of subjects frequently occur. These differences may be due to real effects, random variation or both. It is the job of the experimenter to decide how this variation should be taken note of in the design of the ensuing study, the purpose being that once at the analysis stage, the variation can be partitioned suitably into that due to any real effect of the intervention or real difference between groups, from the random or chance component.
Was this article helpful?