Reverse-Code Item Transform Tool
Explicit reverse item min+max−observed score, on independently validated ordered bounds; not auto reverse from text. Actual independently qualified instrument/cohort/matching units; no diagnosis, causal outcome, validated personal prediction or universal clinical cutoff.
Description
Reverse coding reflects an item score between its scale endpoints.
Reverse coding reflects an item score between its scale endpoints.1
The endpoints must come from the applicable scoring key. The calculation and input requirements are explained below.
When to use Reverse-Code Item Transform Tool
Enter finite minimum and maximum with minimum strictly below maximum, and an observed score inside that inclusive range.
How to use Reverse-Code Item Transform Tool and how it works
- Prepare the measurements or independently established model inputs described below, with matching units and observation scope.
- Enter the required fields and run Reverse-Code Item Transform Tool.
- Read the result fields using the formula, output units, signs and ordering explained below.
- Correct any rejected inputs and rerun; interpret the result within the stated model and its assumptions.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| callerItemMinimum | Caller Item Minimum. Use the units and matching context stated in the calculation below. | number | Required; finite; other constraints below |
| callerItemMaximum | Caller Item Maximum. Use the units and matching context stated in the calculation below. | number | Required; finite; other constraints below |
| actualObservedItemScore | Actual Observed Item Score. Use the units and matching context stated in the calculation below. | number | Required; finite; other constraints below |
Enter finite minimum and maximum with minimum strictly below maximum, and an observed score inside that inclusive range. Return minimum+maximum-score. Reverse-key selection is supplied externally.
reversedScore=minimum+maximum-observedScore Apply the input ordering, units and branch conditions stated above.
| Output field | Meaning | Value type |
|---|---|---|
| result | Object containing the calculated or selected fields below. | object |
| result.value | Numeric result under the formula and output units explained above. | number |
{
"input": {
"callerItemMinimum": 1,
"callerItemMaximum": 5,
"actualObservedItemScore": 2
},
"output": {
"result": {
"value": 4
}
}
}Limitations and assumptions
The calculation uses the supplied observations and model inputs. It does not collect measurements, select a reference population or coefficient, or establish that the model applies to the actual case. The stated branch conditions and output units remain part of the result.
All fields require explicit values. Unexpected fields, wrong types, nonfinite numbers and sparse arrays are rejected. Alignment, bounds and supported-token rules are explained above; extremely large inputs or nonfinite results can also fail. Input errors differ from successful false comparisons, unavailable-domain flags and empty match lists.
Alternative or Complementary methods
Use Likert Sum to Mean Rescaler for a complementary operation: A mean item score divides a scored total by completed items.
Use DASS-21 to DASS-42 Subscale Converter for a complementary operation: Adult DASS-21 subscale totals can be expressed on the conventional DASS-42 metric.
References
-
Reverse-Code Item Transform Tool — tool.io
Similar or alternative tools
- Likert Sum to Mean Rescaler
A mean item score divides a scored total by completed items.
- DASS-21 to DASS-42 Subscale Converter
Adult DASS-21 subscale totals can be expressed on the conventional DASS-42 metric.