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This assignment will help you understand proper reporting and interpretation of a one-way repeated measures ANOVA. You will use the IBM SPSS GLM procedure to accurately compute a repeated measures ANOVA with the wk5data.sav file located below in the Resources. Also use the Data Analysis and Application (DAA) Template located in the Resources to write up your assignment.
Step 1. Write Section 1 of the DAA. Provide a context of the wk5data.sav data set. Specifically, imagine that you are a clinical researcher studying a new treatment for anxiety. To determine treatment efficacy, you monitor the anxiety levels of clients over five weeks. Anxiety symptoms are quantified with a symptom checklist, and the data are entered into SPSS. Week 1 represents the baseline number of anxiety symptoms. Week 5 represents the number of anxiety symptoms at the conclusion of treatment. In Section 1 of the DAA, articulate your within-subjects factor and the outcome variable. Specify the sample size of the data set. Based on your visual inspection of the raw data in wk5data.sav, speculate on the overall trend in recorded symptoms from Week 1 to Week 5.
Step 2. Write Section 2 of the DAA. Assume that the sample is too small to assess multivariate normality. Instead, focus your analysis in Section 2 on the sphericity assumption. Provide the SPSS output for the Mauchly test. Report the results of the Mauchly W and interpret it in terms of the sphericity assumption. If sphericity is violated, analyze the three epsilon estimates (Greenhouse-Geisser, Huynh-Feldt, and lower bound) and justify your decision for selecting one of the three epsilon corrections reported below in Section 4 Interpretation.
Step 3. Write Section 3 of the DAA. Specify a research question related to the repeated measures ANOVA. Articulate the null hypothesis and alternative hypothesis. Specify the alpha level.
Step 4. Write Section 4 of the DAA.
Step 5. Write Section 5 of the DAA. Discuss the conclusions of the repeated measures ANOVA as it relates to the research question. Conclude with an analysis of the strengths and limitations of repeated measures ANOVA.
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