Item quality analysis
Purpose
Inspect item distributions, consistency with the scale and discrimination between high- and low-score groups.
Data and assumptions
Align scoring directions first. Groups are based on the selected-item total. All boundary ties are included, so actual group sizes can exceed the requested fraction.
Configure this method
The default extreme-group fraction is 27%, configurable from 0.10 to 0.49. Overlapping boundary ties or an invariant total prevent a meaningful discrimination test and require checking the data.
Variables
| Control | Input |
|---|---|
| Analysis variables | Select variables |
| Dimensions and items | Add named dimensions and their items |
Analysis settings
| Parameter | Choices | Default |
|---|---|---|
| Also analyze the total scale | Set as needed | Disabled |
| Extreme-group proportion | Set as needed | 0.27 |
Analysis parameters remain visible in the main configuration area. Advanced formatting contains only the table title and numeric decimals. Methods that calculate intervals also show the significance level; 0.05 corresponds to 95% intervals.
Read the results
Consider means, standard deviations, CITC, high-versus-low Welch tests and alpha if deleted together. Retention decisions also require substantive justification.
Workflow and exports
- Upload the dataset and choose the method from the sidebar or search.
- Select the variables above, set the design-specific options, then run the analysis.
- Inspect the paper-style result. Reconfigure from the result area, or open raw output for diagnostics and sample details.
- Rename and keep result tabs as needed. Export Word, Excel, CSV or TXT; batch export can include the selected AI interpretation. Word retains figures. AI text should be checked against the estimates.