Treatment and control groups

In the design of experiments, treatments are applied to experimental units in a treatment group.[1] In comparative experiments, members of a control group receive a standard treatment, a placebo, or no treatment at all.[2] There may be more than one treatment group, more than one control group, or both.

A placebo control group[3][4] can be used to support a double-blind study, in which some subjects are given an ineffective treatment (in medical studies typically a sugar pill) to minimize differences in the experiences of subjects in the different groups; this is done in a way that ensures no participant in the experiment (subject or experimenter) knows to which group each subject belongs. In such cases, a third, non-treatment control group can be used to measure the placebo effect directly, as the difference between the responses of placebo subjects and untreated subjects,[3][4] perhaps paired by age group or other factors (such as being twins).

For the conclusions drawn from the results of an experiment to have validity, it is essential that the items or patients assigned to treatment and control groups be representative of the same population.[5] In some experiments, such as many in agriculture[6] or psychology,[7][8][9] this can be achieved by randomly assigning items from a common population to one of the treatment and control groups.[1] In studies of twins involving just one treatment group and a control group, it is statistically efficient to do this random assignment separately for each pair of twins, so that one is in the treatment group and one in the control group.

In some medical studies, where it may be unethical not to treat patients who present with symptoms, controls may be given a standard treatment, rather than no treatment at all.[2] An alternative is to select controls from a wider population, provided that this population is well-defined and that those presenting with symptoms at the clinic are representative of those in the wider population.[5] Another method to reduce ethical concerns would be to test early-onset symptoms, with enough time later to offer real treatments to the control subjects, and let those subjects know the first treatments are "experimental" and might not be as effective as later treatments, again with the understanding there would be ample time to try other remedies.

See also


  1. Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments, Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9. MR 2363107.
  2. Bailey, R. A. (2008). Design of comparative experiments. Cambridge University Press. ISBN 978-0-521-68357-9. MR 2422352.
  3. Seeley, Ellen W.; Grinspoon, Steven - Harvard Medical School. "Chapter 2: Patient-Oriented Research". Clinical and Translational Science: Principles of Human Research. edited by David Robertson, Gordon H. Williams. p. 13, parag. 3 under "Clinical Trials". Retrieved 2018-07-30.
  4. Chaplin S (2006). "The placebo response: an important part of treatment". Prescriber. 17 (5): 16–22. doi:10.1002/psb.344.
  5. Everitt, B.S. (2002) The Cambridge Dictionary of Statistics, CUP. ISBN 0-521-81099-X (entry for control group)
  6. Neyman, Jerzy (1990) [1923], Dabrowska, Dorota M.; Speed, Terence P. (eds.), "On the application of probability theory to agricultural experiments: Essay on principles (Section 9)", Statistical Science, 5 (4): 465–472, doi:10.1214/ss/1177012031, MR 1092986
  7. Ian Hacking (September 1988). "Telepathy: Origins of Randomization in Experimental Design". Isis. 79 (3): 427–451. doi:10.1086/354775.
  8. Stephen M. Stigler (November 1992). "A Historical View of Statistical Concepts in Psychology and Educational Research". American Journal of Education. 101 (1): 60–70. doi:10.1086/444032.
  9. Trudy Dehue (December 1997). "Deception, Efficiency, and Random Groups: Psychology and the Gradual Origination of the Random Group Design". Isis. 88 (4): 653–673. doi:10.1086/383850. PMID 9519574.
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