How to interpret partial eta squared values for effect size?
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Partial eta squared (ηp2) is an effect size measure that indicates the proportion of variance explained by one or more independent variables in a study. It is commonly used in various fields like soil erosion studies , behavioral sciences , and mixed-effects models . Interpreting partial eta squared involves understanding the amount of variance accounted for by the independent variables relative to the total variance in the study. Higher ηp2 values suggest a stronger effect of the independent variable on the dependent variable, indicating a more substantial impact. Researchers often use ηp2 to assess the practical significance of their findings and to determine the strength of the relationship between variables in their analyses. It is essential to consider ηp2 values in conjunction with other statistical measures to gain a comprehensive understanding of the study results.
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3 Citations | Partial eta squared values for effect size indicate the proportion of variance in the dependent variable explained by a specific independent variable, providing insights into the strength of the relationship. |
7 Citations | The paper introduces flexible methods for estimating partial eta squared in mixed-effects models with crossed random factors, aiding in interpreting effect sizes accurately in complex models. |
91 Citations | Partial eta squared values indicate the proportion of variance explained by independent variables. Higher values suggest a stronger effect size in L2 research, aiding in interpreting the impact of variables. |
| Partial eta squared values for effect size can be interpreted as the proportion of variance explained by the treatment means, heterogeneous variance components, and sample size allocation ratios in ANOVA. | |
44 Citations | Partial eta squared values indicate the proportion of variance in the dependent variable explained by an independent variable, with higher values indicating a stronger effect size in the study. |
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