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m/af/serviet/quiztuizaction 12ckom 1555252849687 0AAABBEE016 8. Measuring effect size for factorial ANOVA Consider the result
soft Edge The researcher performs an analysis of variance (ANOVA) to test the hypothesis that the populations defined by the
m/af/serviet/quiztuizaction 12ckom 1555252849687 0AAABBEE016 8. Measuring effect size for factorial ANOVA Consider the results of a study in which a researcher is interested in the combination of drug types and behavioral therapies for relieving exercise regime) and antidepressants (FeelGood, Cheerup, Energize, and SadNoMore). The researcher defines the first factor as the Aa Aa symptoms. The researcher assigns patients to different types of behavioral programs (cognitive behavioral therapy or reguilar behavioral program and the second factor as the drug type. The results of the hypothetical study are summarized in the data matrix below. Each cell reports the average (8) symptom score 00) on a depression scale. Drug Type FeelGood CheerUp Energize SadNoMore Totals st a 36.5X12 = 39 2 44 22 44.8 82 47.6 24 49.146.38 Sol" 40,25驚02.41.90 Roo-44.80 47.05 Behavioral Program Cognitive Behavioral Therapy Regular Exercise Regime Totals X;,-42 k-40.63 45 The researcher performs an analysis of variance (ANOVA) to test the hypothesis that the populations defined by the treatment combinations are equal. The results are presented in the following ANOVA table. Source Behavioral Therapy661.2520 Drug Type Interaction Error Total df 548.3000 29.0480 4,251.4000 5,490.0000 MS 661.2520 11.20 182.7667 3.10 9.68270.16 59.0472 72 79 Estimate the effect size for the first factor (behavioral program), the second factor (drug type), and the interaction by computing (partial) eta squares. (Express the value of eta square as a percent.) earch
soft Edge The researcher performs an analysis of variance (ANOVA) to test the hypothesis that the populations defined by the treatment combinations are equal. The results are presented in the following ANOVA table. df Source Behavioral Therapy661.2520 Drug Type Interaction Error Total 548.3000 29.0480 4,251.4000 5,490.0000 MS 661.2520 11.20 82.76673.10 9.6827 0.16 59.0472 72 79 Estimate the effect size for the first factor (behavioral program), the second factor (drug type), and the interaction by computing (partial) eta squares. (Express the value of eta square as a percent.) According to these estimates, behavioral program has a effect on depression symptoms than program component. biased estimate than eta squared. Calcullate the effect size estimates for behavioral program, drug Omega squared provides a type, and the interaction by computing (partial) omega squares. (Express the value of omega square as a percent.) earch
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m ve a of the efect sxe Vaotioos vaxiable,s, Bot befove Proceeding , kle need to<no as to hat actl Effect size . Ps a notshelthes fiom theeect gres of OS cakulated Valoes or the variables hle can Say that the efeect gze op act geafest) on the in ДасEffect vio overophy ||| - - 1.252 | sugo 59-6u12-55uq. OLI12. 66 1.25% :0,108524 Dress Type 548-3 = 006608684. Interac Bon 29

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