Understanding the unique health needs of college students and establishing best practices to address them depend, heavily, on the inherent quality and contribution of the research identifying these needs. College health-focused publications currently exemplify less than ideal statistical reporting practices. Specifically, college health…

This brief paper introduces a new approach to assessing the trustworthiness of research comparisons when expressed numerically. The 'number needed to disturb' a research finding would be the number of counterfactual values that can be added to the smallest arm of any comparison before the difference or 'effect' size disappears, minus the number of…

The present article provides a primer on using effect sizes in research. A small heuristic data set is used in order to make the discussion concrete. Additionally, various admonitions for best practice in reporting and interpreting effect sizes are presented. Among these is the admonition to not use Cohen's benchmarks for "small," "medium," and…

According to some researchers canonical correlation results should be interpreted in part by consulting redundancy coefficients (Rd). This paper, however, makes the case that Rd coefficients generally should not be interpreted. Rd coefficients are not multivariate. Furthermore, it makes little sense to interpret coefficients not optimized as part…

This paper illustrates how canonical correlation analysis can be employed to implement all the parametric tests that canonical methods subsume as special cases. The point is heuristic: all analyses are correlational, all apply weights to measured variables to create synthetic variables, and all yield effect sizes analogous to "r"…