Regression to the mean: what it is and how to deal with it

• Published in: International journal of epidemiology Vol. 34; no. 1; pp. 215 - 220
• Main Authors: Barnett, Adrian G, van der Pols, Jolieke C, Dobson, Annette J
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 01-02-2005; Oxford Publishing Limited (England)
• Subjects: Analysis. Health state; Biological and medical sciences; Cholesterol, HDL - blood; clinical trials; Clinical Trials as Topic - methods; Data Interpretation, Statistical; epidemiological research design; Epidemiology; General aspects; Humans; intervention; longitudinal studies; Medical sciences; observational studies; Public health. Hygiene; Public health. Hygiene-occupational medicine; Regression Analysis; Regression to the mean; repeated measures; Research Design; Skin Neoplasms - prevention & control; statistics; epidemiological research design; Research; Epidemiology; repeated measures; Statistical method; Statistical regression; Clinical trial; Regression to the mean; clinical trials; intervention; observational studies; Public health; longitudinal studies; statistics
• ISSN: 0300-5771; 1464-3685; 1464-3685
• DOI: 10.1093/ije/dyh299

Background Regression to the mean (RTM) is a statistical phenomenon that can make natural variation in repeated data look like real change. It happens when unusually large or small measurements tend to be followed by measurements that are closer to the mean. Methods We give some examples of the phenomenon, and discuss methods to overcome it at the design and analysis stages of a study. Results The effect of RTM in a sample becomes more noticeable with increasing measurement error and when follow-up measurements are only examined on a sub-sample selected using a baseline value. Conclusions RTM is a ubiquitous phenomenon in repeated data and should always be considered as a possible cause of an observed change. Its effect can be alleviated through better study design and use of suitable statistical methods.