What do we mean by "regression toward the mean"?

"Regression toward the mean" refers to the statistical phenomenon where extreme observations on a variable are likely to be followed by values that are closer to the average or mean on subsequent measurements. This concept arises largely from the understanding that many factors can influence a measurement, and those that cause extreme values may not be consistent across measurements. For example, if a person scores unusually high or low on a test, it is likely that in a retest, their score will be closer to the average score of the population, rather than staying at that extreme level.

This means that if we measure something and find something very high or very low, it is expected that the next measurement will be more moderate or average, reflecting a natural variability rather than an inherent extreme condition. This concept is particularly important in healthcare and statistics when designing studies or interpreting data, as it helps in understanding how individual measurements are subject to fluctuations and how outcomes can normalize over time or across measurements.