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Effect size for post-hoc-tests of the Repeated Measures ANOVA in SPSS
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After significant post-hoc-tests for the repeated measures ANOVA in SPSS an effect size calculation is highly recommended. Since post-hoc-testing for the repeated measures ANOVA is doing pairwise dependent t-tests, the proper effect size is Cohen's d.
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The magnitude of the effect size is classified with comparable studies or research field specific thresholds. If neither exist, you can refer to Cohen (1992): A Power Primer on page 157.
📚 Literature:
===========
- Cohen, J. (1992): Quantitative methods in psychology: A power primer. Psychological bulletin, pp. 155-159.
- Wasserstein, R. L., & Lazar, N. A. (2016). The ASA statement on p-values: context, process, and purpose. The American Statistician, 70(2), 129-133.
⏰ Timestamps:
==============
0:00 Introduction and prerequisites
0:21 Calculating Cohen's d with different standardizers
2:09 Classifying Cohen's d with different standardizers
If you have any questions or suggestions regarding Effect size for post-hoc-tests of the repeated measures ANOVA in SPSS, please use the comment function. Thumbs up or down to decide if you found the video helpful.
#statorials
Support channel? 🙌🏼
===================
➡️ Watch next: UPCOMING
The magnitude of the effect size is classified with comparable studies or research field specific thresholds. If neither exist, you can refer to Cohen (1992): A Power Primer on page 157.
📚 Literature:
===========
- Cohen, J. (1992): Quantitative methods in psychology: A power primer. Psychological bulletin, pp. 155-159.
- Wasserstein, R. L., & Lazar, N. A. (2016). The ASA statement on p-values: context, process, and purpose. The American Statistician, 70(2), 129-133.
⏰ Timestamps:
==============
0:00 Introduction and prerequisites
0:21 Calculating Cohen's d with different standardizers
2:09 Classifying Cohen's d with different standardizers
If you have any questions or suggestions regarding Effect size for post-hoc-tests of the repeated measures ANOVA in SPSS, please use the comment function. Thumbs up or down to decide if you found the video helpful.
#statorials
Support channel? 🙌🏼
===================