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This is because the splitting of items (as necessary to resolve DIF) results in structural missing cases.
If a second construct was significant and large, and represented by more than three items, deletion of items or splitting of items and construction of two related but different outcome measures was considered.
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It should be noted that the splitting of data items can be tricky as SNOMED CT does include some concepts that refer to multiple clinical conditions such as "26298008|Diabetic coma with ketoacidosis (disorder)|".
No DIF could explain this misfit and guide split of the items, hence these items were removed.
This pattern was similar also when considering fit statistics after successive splitting of each item one at a time.
Improvement of fit by split of the items with DIF was explored before removing items.
The algorithms of this decision tree usually work top-down by choosing a variable at each step that is the next best variable to use in splitting the set of items.
However, as this DIF did not cause significant misfit of the item, and split of the item did not improve fit, it was kept without split in the subscale.
While the HC is designed for all home care clients, the CHA splits out a set of items from the HC that are appropriate for light-care clients.
The first approach followed a standard procedure for split-half analysis in which the OLQ-13 was split into halves based on order of items (resulting in a test half consisting of items a to g and a test half with items h to m).
The sum was divided by the number of items and then split into thirds with tertiles as cut-off points.
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