In epidemiologic studies, the measurement of characteristics of interest is almost always subject to random measurement error. This error and its effects are usually overlooked by researchers. One of its effects is a widespread statistical phenomenon that is well known as regression to the mean. This phenomenon occurs whenever an extreme group of people is selected from a population based on their measurements of a variable. If a second measurement is taken in this group, the mean of the second measurement will be closer to the mean of the population. In interventional studies, this increase (decrease) might be regarded as the effect of intervention, when in fact it has had no effect. Ignoring regression to the mean will lead to the erroneous conclusions and interpretation of the results of epidemiologic studies and affects the decisions in evidence-based medicine and planning for preventive and public health measures. This paper highlights the importance of this problem and its effects in epidemiologic studies and the ways to avoid it.
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