Generalized eta and omega squared statistics: measures of effect size for some common research designs.

By Stephen Olejnik, James Algina. Psychological methods, 2003

1,529 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/1fb92847d0c205cd83c0c9c252b4e6090281f44d

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

In Developmental and Educational Psychology

In Management Science and Operations Research

Citations in the corpus

The Meaningfulness of Effect Sizes in Psychological Research: Differences Between Sub-Disciplines and the Impact of Potential Biases (2019, neutral): “This is particularly true for values of η2p when these come from designs that might, for instance, additionally include covariates (Olejnik and Algina, 2003).”
A Simple Method for Removing Bias From a Popular Measure of Standardized Effect Size: Adjusted Partial Eta Squared (2019, background): “…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 effect size.2 In…”
Effect Sizes for Growth-Modeling Analysis for Controlled Clinical Trials in the Same Metric as for Classical Analysis (2009, methodology): “…M anuscript N IH -PA Author M anuscript Conclusions Researchers who conduct controlled clinical trials need to calculate effect sizes that are comparable across studies and suitable for inclusion in meta-analyses that combine studies using different statistical designs (Olejnik & Algina, 2003).”
Gamma and beta bursts underlie working memory (2016, positive): “The bias-corrected PEV (Olejnik and Algina, 2003; Buschman et al., 2011) was estimated from average firing rates in 50-ms bins across trials with different”
Moving on up: can results from simple aquatic mesocosm experiments be applied across broad spatial scales? (2011, methodology): “From the 3-way ANOVAs, we calculated the magnitude of main and interactive effects (x2, per cent variance explained [Olejnik & Algina, 2003; Duffy, Richardson & France, 2005; Spivak et al., 2007, 2009a)].”
Effect size estimates: current use, calculations, and interpretation. (2012, methodology): “Advice on calculating G 2 can be found in Olejnik and Algina (2003). Radj 2 and .”
Are males always better than females in mental rotation? Exploring a gender belief explanation (2009, background): “As to eta squared, it depends on the design and on the number and kind of factors (Olejnik & Algina, 2003).”
Prefrontal Cortex Networks Shift from External to Internal Modes during Learning (2016, methodology): “A linear model was fit to spike rates separately for each neuron, time point, and trial window and was used to compute the percentage of variance explained (PEV) by each factor, using the bias-corrected -squared formulation (Olejnik and Algina, 2003).”
Applied MANOVA and discriminant analysis (2006, methodology): “[Note that with the repeated measures design, N is the total number of measurements in the data set, not the number of subjects (Olejnik and Algina, 2003).”
A Comparison of Three-Step Approaches for Auxiliary Variables in Latent Class and Latent Profile Analysis (2017, methodology): “Therefore, we used a mixed-design analysis of variance (ANOVA) and generalized eta squared (G η2) (Olejnik & Algina, 2003) measure of effect size to sort manipulated conditions with respect to the magnitude of their effect on relative bias of coefficient estimates, relative standard error bias,…”
Method for the subjective assessment of intermediate quality level of (2014, background): “A discussion of alternative measures of association strength can be found in Olejnik and Algina [31].”
Technology-Market Combinations and the Identification of Entrepreneurial Opportunities: An Investigation of the Opportunity-Individual Nexus (2012, methodology): “…effects of increases in superficial and structural similarity are sufficiently important in magnitude to be meaningful, we calculated estimates of partial eta-square ( 2p) and of the more conservative generalized etasquare ( 2G) (cf. Olejnik & Algina, 2003; Pierce, Block, & Aguinis, 2004).”
Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA (2015, methodology): “Omega-squared (x(2)) provides a less biased measure of effect size for ANOVA-type analyses by accounting for the mean-squared error (Olejnik and Algina, 2004; Ziegler and Bühner, 2009) of the observed samples,”