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Averaging Effect Sizes Within and Across Studies of Interventions Aimed at Improving Child Outcomes
Author(s) -
Dong Nianbo,
Maynard Rebecca A.,
PerezJohnson Irma
Publication year - 2008
Publication title -
child development perspectives
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3
H-Index - 71
eISSN - 1750-8606
pISSN - 1750-8592
DOI - 10.1111/j.1750-8606.2008.00064.x
Subject(s) - psychological intervention , transparency (behavior) , psychology , work (physics) , field (mathematics) , applied psychology , management science , cognitive psychology , computer science , economics , engineering , mechanical engineering , computer security , mathematics , psychiatry , pure mathematics
—Scientific and political forces are moving the social services field toward greater reliance on evidence‐based interventions or strategies, including in the area of child development. This article draws on the work of meta‐analysts to illustrate how study findings can sometimes be made more accessible to policy makers and practitioners by converting them to effect sizes and averaging them within or across studies. The article first introduces the concept of an effect size. Using empirical examples, it then illustrates the mechanics of computing average effect sizes and discusses their benefits and limitations as summary measures of the estimated effects of interventions. It also provides guidance regarding when it is appropriate to pool findings across studies and how to display results to promote transparency.