Recommended effect size statistics for repeated measures designs
By R. Bakeman. Behavior Research Methods, 2005
1,709 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Developmental and Educational Psychology, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/439eeea85a51f52d282f47ffdc683ec933c77532
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
- E. Clark
- Maya Sugita McEown
- Jeffrey D. Long
- Elizabeth R. Brown
- Kimberly A. Noels
- E. Razumiejczyk
- Guillermo Macbeth
- Jordan W Smith
In Developmental and Educational Psychology
- R. Norouzian
- Kristie Saumure
- E. Clark
- Maya Sugita McEown
- Jeffrey D. Long
- Elizabeth R. Brown
- Kimberly A. Noels
- Jordan W Smith
In Management Science and Operations Research
- R. Norouzian
- J. Toby Mordkoff
- E. Clark
- Maya Sugita McEown
- Jeffrey D. Long
- Elizabeth R. Brown
- Kimberly A. Noels
- E. Razumiejczyk
Citations in the corpus
- Students' self-determined and integrative orientations and teachers' motivational support in a Japanese as a foreign language context (2014, positive): “These results showed a significant effect, F(3.21, 401.08) ¼ 238.85, p < .01, and a very large effect size (hp2 ¼ .66; see Bakeman, 2005,7).”
- An exploratory study of perceived safety in a neighborhood park using immersive virtual environments (2018, methodology): “a Generalized Eta-Squared measure of effect size (Bakeman, 2005).”
- Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs (2013, methodology): “In between-subjects designs with fixed factors ω2 and ω2p can be calculated through the formulas provided by Olejnik and Algina (2000) and Bakeman (2005): ω2 = df effect × (MSeffect − MSerror) SStotal + MSerror (14) ω2p = df effect × (MSeffect − MSerror) df effect × MSeffect + (N − df effect) ×…”
- Eta- and partial eta-squared in L2 research: A cautionary review and guide to more appropriate usage (2018, background): “However, we now may have multiple sources of independent effects leading to a distinction that must be drawn between the classical η2 and partial η2 (e.g. Bakeman, 2005; Richardson, 2011).”
- Seeking Congruity Between Goals and Roles (2010, methodology): “Main and lower-order effects were omitted from this summary for brevity, and the effect sizes for critical interactions were calculated in the generalized eta-squared statistic (Bakeman, 2005).”
- Developmental changes in hypothalamus–pituitary–adrenal activity over the transition to adolescence: Normative changes and associations with puberty (2009, background): “07 (Bakeman, 2005), there were no significant interaction effects of trials with gender or age group.”
- Spatial Training Improves Children's Mathematics Ability (2014, background): “For this measure, .02 is considered a small effect, .13 is considered a medium effect, and .26 is considered a large effect (Bakeman, 2005; Cohen, 1988). to show significant improvement on any of the math subskills: missing term, t(26)¼ 1.19, p¼ .13; multidigit, t(26)¼ 0.49, p¼ .32; number fact,…”
- The Empirical Verification of an Assignment of Items to Subtests (2008, methodology): “…independent variables that were most influential to the proportions of correct judgments for both the correct and incorrect assignments, we considered the values of the partial Z2, resulting from repeated measures analyses of variance (RMANOVAs), as a measure of effect size (e.g., Bakeman, 2005).”
- A Simple Method for Removing Bias From a Popular Measure of Standardized Effect Size: Adjusted Partial Eta Squared (2019, background): “…detailed, statistical discussions (e.g., Carroll & Nordholm, 1975; Grissom & Kim, 2012; Hays, 1963; Keppel, 1991; Maxwell & Delaney, 2004; see also Bakeman, 2005; Olejnik & Algina, 2003), neither of these alternatives has come close to supplanting η p 2 as the dominant measure of standardized…”
- Cliff's Delta Calculator: A non-parametric effect size program for two groups of observations (2010, background): “Sample size, homogeneity of variances, data normality, and effect size estimation, among many others, are important issues that critically impact on the quality of the evidence (Bakeman, 2005; Grissom & Kim, 2005; Strube, 2006).”