The randomised control trial (RCT) is a trial in which subjects are randomly assigned to one of two groups: one (the experimental group) receiving the intervention that is being tested, and the other (the comparison group or control) receiving an alternative (conventional) treatment (fig 1). The two groups are then followed up to see if there are any differences between them in outcome. The results and subsequent analysis of the trial are used to assess the effectiveness of the intervention, which is the extent to which a treatment, procedure, or service does patients more good than harm. RCTs are the most stringent way of determining whether a cause-effect relation exists between the intervention and the outcome.


  • Good randomization will "wash out" any population bias
  • Easier to blind/mask than observational studies
  • Results can be analyzed with well known statistical tools
  • Populations of participating individuals are clearly identified


  • Expensive in terms of time and money
  • Volunteer biases: the population that participates may not be representative of the whole
  • Loss to follow-up attributed to treatment

This discusses various key features of RCT design, with particular emphasis on the validity of findings. There are many potential errors associated with health services research, but the main ones to be considered are bias, confounding, and chance.

  • Bias is the deviation of results from the truth, due to systematic error in the research methodology. Bias occurs in two main forms: (a) selection bias, which occurs when the two groups being studied differ systematically in some way, and (b) observer/information bias, which occurs when there are systematic differences in the way information is being collected for the groups being studied.
  • confounding factor is some aspect of a subject that is associated both with the outcome of interest and with the intervention of interest. For example, if older people are less likely to receive a new treatment, and are also more likely for unrelated reasons to experience the outcome of interest, (for example, admission to hospital), then any observed relation between the intervention and the likelihood of experiencing the outcome would be confounded by age.
  • Chance is a random error appearing to cause an association between an intervention and an outcome. The most important design strategy to minimise random error is to have a large sample size.
  • These errors have an important impact on the interpretation and generalisability of the results of a research project. The beauty of a well planned RCT is that these errors can all be effectively reduced or designed out . The appropriate design strategies will be discussed below.


Thanks and Regards,


Associate Editor

Journal of Clinical Trials