"Researchers have looked at comparisons between medical epidemiological research and psychological research using effect size r in an effort to compare relative effects. Often the outcomes of such efforts have demonstrated comparatively low effects for medical epidemiology research in comparison with effect sizes seen in psychology. The conclusion has often been that relatively small effects seen in psychology research are as strong as those found in important epidemiological medical research. The author suggests that many of the calculated effect sizes from medical epidemiological research on which this conclusion has been based are flawed. Specifically, rather than calculating effect sizes for treatment, many results have been for a Treatment Effect × Disease Effect interaction that was irrelevant to the main study hypothesis. A technique for developing a “hypothesis-relevant” effect size r is proposed."

I _told_ you so. (Though they are _shockingly_ naive about fMRI and brain organization.)

Shorter Peterson: Your results look like a factor analysis of pure noise. Have a nice day. (Also, a citation in support of the folk wisdom that factor analysis doesn't work any better as data reduction than simple principal components analysis.)

Since (to indulge in self-quotation) about the only thing in actual cognitive psychology which correlates well with "g" is working memory capacity, it's not exactly astonishing that memory training improves measured "g". (But it is a non-trivial finding nonetheless because the memory training does transfer across tasks.)

"Dude! R^2 sux!" (I paraphrase.)

"From 1962–1967, at ages 3 and 4, the subjects were randomly divided into a program group that received a high-quality preschool program based on High/Scope's participatory learning approach and a comparison group who received no preschool program. ..."