The article by Roger Bakeman discusses the importance of reporting effect size statistics in psychological research, particularly in the context of repeated measures designs. It highlights the limitations of traditional effect size measures like eta squared (η²) and partial eta squared (ηp²) in such designs and introduces generalized eta squared (ηG²) as a more versatile and comparable measure. ηG² is proposed as the preferred statistic for reporting effect sizes in ANOVAs with repeated measures, as it accounts for both between-subjects and within-subjects factors, ensuring comparability across different study designs. The article explains the computation of ηG² using standard statistical software like SPSS and provides examples to illustrate its application. It emphasizes the practical benefits of using ηG² for researchers, including its ease of computation and its ability to provide meaningful effect size estimates across studies. The author also discusses the importance of discussing effect sizes in research reports to enhance the cumulative knowledge in the field.The article by Roger Bakeman discusses the importance of reporting effect size statistics in psychological research, particularly in the context of repeated measures designs. It highlights the limitations of traditional effect size measures like eta squared (η²) and partial eta squared (ηp²) in such designs and introduces generalized eta squared (ηG²) as a more versatile and comparable measure. ηG² is proposed as the preferred statistic for reporting effect sizes in ANOVAs with repeated measures, as it accounts for both between-subjects and within-subjects factors, ensuring comparability across different study designs. The article explains the computation of ηG² using standard statistical software like SPSS and provides examples to illustrate its application. It emphasizes the practical benefits of using ηG² for researchers, including its ease of computation and its ability to provide meaningful effect size estimates across studies. The author also discusses the importance of discussing effect sizes in research reports to enhance the cumulative knowledge in the field.