What Are Effect Sizes and Why Do We Need Them

By L. Hedges. 2008

118 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Social Psychology, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/efdc0708b5fe5c96d70cbf75df9a853818eeb464

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. M. Hogg
2. Nicolas Barreto
3. Gabriele Gratton
4. Suzanne E. Mol
5. A. Bus
6. M. Kraft

In Social Psychology

1. Nicolas Barreto
2. M. Hogg
3. J. Richard
4. P. Mallet
5. Barry H. Schneider
6. Suzanne E. Mol
7. A. Bus
8. M. Kraft

In Sociology and Political Science

1. Nicolas Barreto
2. M. Hogg
3. Suzanne E. Mol
4. A. Bus
5. M. Kraft
6. D. van Knippenberg
7. David de Cremer
8. Barbara van Knippenberg

Citations in the corpus

• Committee report: publication guidelines and recommendations for studies using electroencephalography and magnetoencephalography. (2014, background): “Effect sizes may be large yet not very useful, or small but theoretically or pragmatically important (Hedges, 2008).”
• To read or not to read: a meta-analysis of print exposure from infancy to early adulthood. (2011, methodology): “Effect sizes, quantitative indexes of relations among variables, are used to compare and communicate the strength of the summarized research findings (Hedges, 2008).”
• Evaluation of and support for group prototypical leaders: a meta-analysis of twenty years of empirical research (2017, methodology): “This measure of effect size is chosen for two reasons; it is the more common in the literature concerning prototypicality and leader ratings, and these latter constructs are generally measured on a Likert scale, and are therefore continuous data (Durlak, 2009; Hedges, 2008).”
• Interpreting Effect Sizes of Education Interventions (2020, methodology): “…enthusiastic, consider this: By fifth grade, student achievement improves about 0.40 SD or less over the course of an academic year (Bloom et al., 2008), and schools only account for around 40% of these achievement gains (Chingos et al. 2015; Konstantopolus & Hedges, 2008; Luyten et al., 2017).”
• Revisiting the whole-school approach to bullying: Really looking at the whole school (2012, background): “Thus, the standardized beta coefficients indicated the relative change in the outcome variables that was associated with a one-unit change in the predictors, and were considered measures of effect size (Hedges, 2008).”
• When combinations of humans and AI are useful: A systematic review and meta-analysis (2024, unknown): “The studies in our dataset, though, come from different samples of people—some look at doctors 37–39 , others at crowdworkers 4,6,34 and still others at students 13,40,41 —and this variation can limit the comparability of the effect sizes to a degree 36 .”