How to Conduct a Mixed ANOVA
Use a mixed ANOVA when you want to measure the difference in one outcome between two or more time periods and between two or more groups.
Step 1: Access the Mixed ANOVA Tool
- Click T-test & Mixed ANOVA in the sidebar menu.
- Check Paired t-test / Repeated & Mixed ANOVA.
Step 2: Configure Your Analysis
- Enter the number of time points (e.g., 2 = pretest, posttest; 3 = test 1, test 2, test 3).
- Choose the time 1 variable (first time, e.g., pretest, test 1).
- Choose the time 2, 3, 4, 5, 6 variables as needed.
- Choose the group variable (group with categories, e.g., churn, fraud, quitting).
- Click Apply variables.
Step 3: Run the ANOVA
- Click Enable stat mode to run the ANOVA.
- See the values of the dependent variable for each time point in each group.
Step 4: Interpret the Results
- Scroll down to Averisys AI and click Results to review key outputs:
- Review the F-value, degrees of freedom, and p-value.
- Describe the direction and magnitude of the difference (e.g., mean Revenue in the churn-prone group is lower in the posttest).
- p-value < 0.05 — statistically significant difference over time between groups.
- p-value ≥ 0.05 — no significant difference detected.
Step 5: Report Your Findings
- Develop action plans based on insights.
- Click Reports to see the executive summary.
- Click Publish this page to share results with stakeholders via a published page.
- Click Invite Users to invite stakeholders to share results via dashboards.
Example Interpretation
- The mixed ANOVA showed a significant interaction between Fraud status and Time on Revenue (F(2, 196) = 5.21, p = 0.007), indicating that the change in Revenue over time differed between fraudulent and non-fraudulent groups.
If something does not work as described
Screens are updated as the platform changes, so a button may sit in a slightly different place than the wording above suggests. When that happens, the AI assistant inside the platform is the fastest way forward: it can see the page being worked on and answer in context, at any hour. Ask it what a message means, why a file was rejected, or which step comes next.
Most problems in this part of the workflow come from the data rather than the platform. Column headers that repeat, numbers stored as text, blank rows at the bottom of a file, and inconsistent category labels are the usual causes. Checking those four things resolves the majority of failed uploads and unexpected results before any further troubleshooting is needed.
For anything that still does not resolve, email support@averisysanalytics.com with the guide title, the step reached, and what appeared instead of the expected result. Including the file name and a screenshot usually means the issue is answered in the first reply. Related instructions are listed in the full platform guide, and common questions are collected in the support FAQ.