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Answer :
Effect size in a factorial ANOVA is measured to quantify the magnitude of treatment effects for depression, helping to understand the practical significance rather than just statistical significance. Hence, option 2) To quantify the magnitude of the treatment effects is the correct answer.
The purpose of measuring effect size in a study of different treatments for depression, namely drug types and behavioral therapies, is not to determine the statistical significance of the results, but rather to quantify the magnitude of the treatment effects. ANOVA, or Analysis of Variance, helps us understand if there is a significant difference between groups, but effect size tells us how large that difference is. Specifically, in the context of a factorial ANOVA, effect size would indicate how much the drug type and therapy individually, as well as in combination, account for variations in depressive symptom relief.
While statistical significance informs us that an effect exists, effect size provides insight into the practical significance of that effect. For example, finding out that a therapy is significantly more effective than no treatment might be less informative without knowing whether the improvement is small or substantial. Thus, effect size is crucial for understanding the real-world implications of the findings from the study. Hence, option 2) To quantify the magnitude of the treatment effects is the correct answer.
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