Читать книгу Applied Univariate, Bivariate, and Multivariate Statistics - Daniel J. Denis - Страница 77

The solution to episodes of misunderstanding the significance test is not to drop or ban it, contrary to what some have recommended (e.g., Hunter, 1997). Rather, the solution is to supplement it with a measure that accounts for the actual distance between means and serves to convey the magnitude of the actual scientific finding, as opposed to statistical finding, should there be one. Measures of effect size, interpreted in conjunction with significance tests, help to communicate whether something has “happened” or “not happened” in the given study or experiment. The reader interested in effect sizes can turn to a multitude of sources (Cortina and Nouri, 1999; Rosenthal, Rosnow, and Rubin, 2000). For our purposes, it suffices to review the principle of an effect size measure rather than catalog the wealth of possibilities for effect sizes available. Perhaps the easiest and most straightforward way of conceptualizing an effect size is to consider a measure of standardized statistical distance, or Cohen's d, already featured in our computations of power.