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Article

Effect sizes in memory research

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Pages 832-842 | Received 02 Dec 2011, Accepted 03 Jan 2013, Published online: 25 Jan 2013
 

Abstract

Effect sizes are omitted from many research articles and are rarely discussed. To help researchers evaluate effect sizes we collected values for the more commonly reported effect size measures (partial eta squared and d) from papers reporting memory research published in 2010. Cohen's small, medium, and large generic guideline values for d mapped neatly onto the observed distributions, but his values for partial eta squared were considerably lower than those observed in current memory research. We recommend interpreting effect sizes in the context of either domain-specific guideline values agreed for an area of research or the distribution of effect size estimates from published research in the domain. We provide cumulative frequency tables for both partial eta squared and d enabling authors to report and consider not only the absolute size of observed effects but also the percentage of reported effects that are larger or smaller than those observed.

Some of the contents of this paper were presented at the ICOM5 conference, York, UK, August 2011 and some at the 53rd Annual Meeting of the Psychonomic Society, Minneapolis, MN, November 2012.

Some of the contents of this paper were presented at the ICOM5 conference, York, UK, August 2011 and some at the 53rd Annual Meeting of the Psychonomic Society, Minneapolis, MN, November 2012.

Notes

1 Cohen's d is used here to refer to the standardised difference between the means, whether the difference is standardised on the population standard deviation (Cohen, Citation1962, Citation1988) or the pooled standard deviation (Hedges's g; Hedges, Citation1982). Most researchers refer to d even when they have actually calculated g, and g is sometimes used to refer to an unbiased estimate (e.g., Borenstein, Hedges, Higgins, & Rothstein, Citation2009). It is always wise to clearly specify the specific calculation when reporting d to avoid unnecessary ambiguity.

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