Effect of regression to the mean on decision making in health care
BMJ 2003; 326 doi: https://doi.org/10.1136/bmj.326.7398.1083 (Published 15 May 2003) Cite this as: BMJ 2003;326:1083
- Veronica Morton, research fellow1,
- David J Torgerson (djt6@york.ac.uk), director1
- 1 York Trials Unit, Department of Health Sciences, University of York, York YO10 5DD
- Correspondence to: Dr Torgerson
- Accepted 5 March 2003
Knowledge of regression to the mean can help with everything from interpreting test results to improving your career prospects. All healthcare professionals should be aware of its implications
Regression to the mean is a widespread statistical phenomenon with potentially serious implications for health care. It can result in wrongly concluding that an effect is due to treatment when it is due to chance. Ignorance of the problem will lead to errors in decision making. We discuss the importance of the issue and its effects on many common clinical, public health, and managerial decisions.
What is regression to the mean?
Regression to the mean occurs whenever a nonrandom sample is selected from a population and two imperfectly correlated variables are measured, such as two consecutive blood pressure measurements. The less correlated the two variables, the larger the effect of regression to the mean. Also, the more extreme the value from the population mean, the more room there is to regress to the mean. It occurs whenever a group is selected with extreme values for one variable and another variable is then measured.1 2
Francis Galton documented the phenomenon in 1886. Galton measured the height of 930 adult children and their parents and calculated the average height of the parents. He noted that when the average height of the parents was greater than the mean of the population, the children tended to be shorter then the parents. Likewise, when the average height of the parents was shorter than the population mean, the children tended to be taller than their parents. Galton called this phenomenon regression towards mediocrity, and it is now known as regression to the mean.3
Ignorance of this phenomenon is widespread. …
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