Abstract
It is common in repeated measurements for extreme values at the first measurement to approach the mean at the subsequent measurement, a phenomenon called regression to the mean (RTM). If RTM is not fully controlled, it will lead to erroneous conclusions. The wide use of repeated measurements in social psychology creates a risk that an RTM effect will influence results. However, insufficient attention is paid to RTM in most social psychological research. Notable cases include studies on the phenomena of social conformity and unrealistic optimism (Klucharev et al., 2009, 2011; Sharot et al., 2011, 2012b; Campbell-Meiklejohn et al., 2012; Kim et al., 2012; Garrett and Sharot, 2014). In Study 1, 13 university students rated and re-rated the facial attractiveness of a series of female faces as a test of the social conformity effect (Klucharev et al., 2009). In Study 2, 15 university students estimated and re-estimated their risk of experiencing a series of adverse life events as a test of the unrealistic optimism effect (Sharot et al., 2011). Although these studies used methodologies similar to those used in earlier research, the social conformity and unrealistic optimism effects were no longer evident after controlling for RTM. Based on these findings we suggest several ways to control for the RTM effect in social psychology studies, such as adding the initial rating as a covariate in regression analysis, selecting a subset of stimuli for which the participant' initial ratings were matched across experimental conditions, and using a control group.
Highlights
Researchers often make repeated measurements on unstable variables to obtain more accurate data or to assess change
As is common in social psychological research, earlier studies on the social conformity effect and the unrealistic optimism effect have relied on repeated measurements but have not fully controlled for the effects of regression to the mean” (RTM)
In the current studies we demonstrated that the social conformity effect and unrealistic optimism effect were remarkable before controlling for RTM but were no longer apparent after controlling for RTM
Summary
Researchers often make repeated measurements on unstable variables to obtain more accurate data or to assess change. Measurements vary from one time point to the due to random error, and extreme values at the first measurement tend to approach the mean at the subsequent measurement This is known as “regression to the mean” (RTM) (Galton, 1886). If a large group of students is given a test of some sort and the top-performing 10% students are selected, these people would be likely to score worse, on average, if re-tested. This is because their performance in a single test reflects individuals’ true skill plus some luck rather than their normal level ability in most circumstances. This has been recognized by many clinical researchers as treatments that appear to be efficacious may not show evidence of efficacy once RTM is controlled (Whitney and Von Korff, 1992; Cummings et al, 2000; Morton and Torgerson, 2003)
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