title: Regression to the mean. A threat to exercise science?
abstract: Regression to the mean (RTM) can bias any investigation where the response to treatment is classified relative to initial values for a given variable without the use of an appropriate control group. The phenomenon and resulting errors of interpretation have been recognised by clinicians in a number of disciplines. The causes of RTM include both intra-individual variance and measurement error. The magnitude of RTM can be estimated quite simply, given a knowledge of intra- and inter-individual variance. RTM can be avoided by using a fully controlled experimental design. Difficulties can also be minimised by making duplicate measurements prior to the experimental manipulation, the first measurement serving for classification, and the second (with randomly distributed variance) allowing an assessment of the response to treatment. Less satisfactorily, surrogate measurements (for example, plasma volume for maximal oxygen intake [VO2(max)]) can assess the bias introduced by an initial non-random sorting of study participants. The impact of RTM on the design and interpretation of investigations has as yet received little consideration by exercise scientists and sports physicians. The response to training is often related to initial measurements of a dependent variable such as heart size, ST segmental depression, fitness or level of physical activity. In particular, analyses of this type have been adduced to support the belief that the response to aerobic training is inversely related to an individual's VO2(max). In fact, RTM may account for a major part of this apparent relationship.
authors.affiliation: Department of Public Health Sciences, Faculty of Physical Education and Health, University of Toronto, Toronto, Ontario, Canada. royjshep@shaw.ca
authors.forename: Roy J
authors.initials: RJ
authors.lastname: Shephard
mesh_terms: D005081:Exercise Therapy / Q000706:statistics & numerical data*; D006801:Humans; D012044:Regression Analysis; D012107:Research Design; D013178:Sports Medicine / Q000706:statistics & numerical data*