Personality psychologists wallow in effect size; the ubiquitous correlation coefficient, Pearson’s r, is central to nearly every research finding they report. As a consequence, discussions of relationships between personality variables and outcomes are routinely framed by assessments of their strength. For example, a landmark paper reviewed predictors of divorce, mortality, and occupational achievement, and concluded that personality traits have associations with these life outcomes that are as strong as or stronger than traditional predictors such as socio-economic status or cognitive ability (Roberts et al., 2007). This is just one example of how personality psychologists routinely calculate, care about, and even sometimes worry about the size of the relationships between their theoretical variables and their predicted outcomes.
Social psychologists, not so much. The typical report in experimental social psychology focuses on p-level, the probability of the magnitude of the difference between experimental groups occurring if the null hypothesis of no difference were to be true. If this probability is .05 or less, then: Success! While effect sizes (usually Cohen’s d or, less often, Pearson’s r) are reported more often they they used to be – probably because the APA Publication Manual explicitly requires it (a requirement not always enforced) – the emphasis of the discussion of the theoretical or even the practical importance of the effect typically centers around whether it exists. The size simply doesn’t matter.
Is this description an unfair caricature of social psychological research practice? That’s what I thought until recently. Continue reading →
