Cliff Delta Nonoverlap Calculator
Cliffδpairwise wins minus losses overNpairs, ties zero, higher first direction. Distinct from proportion-only common language effect or all-curves temporal nonoverlap. Actual independently qualified instrument/cohort/matching units; no diagnosis, causal outcome, validated personal prediction or universal clinical cutoff.
Description
Cliff's delta compares all cross-group observation pairs.
Cliff's delta compares all cross-group observation pairs.1
Wins and losses establish a signed dominance contrast, with ties contributing zero. The calculation and input requirements are explained below.
When to use Cliff Delta Nonoverlap Calculator
Enter two nonempty observation lists with at most 1000000 cross-group pairs.
How to use Cliff Delta Nonoverlap Calculator 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 Cliff Delta Nonoverlap Calculator.
- 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 |
|---|---|---|---|
| actualFirstGroupObservations | Actual First Group Observations. Use the units and matching context stated in the calculation below. | array of number | Required; other constraints below |
| actualSecondGroupObservations | Actual Second Group Observations. Use the units and matching context stated in the calculation below. | array of number | Required; other constraints below |
Enter two nonempty observation lists with at most 1000000 cross-group pairs. Score each pair +1 when first exceeds second, -1 when lower and 0 when equal. Average across every pair. The output is signed dominance rather than temporal curve nonoverlap.
delta=(wins-losses)/pairCount 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": {
"actualFirstGroupObservations": [
2,
3
],
"actualSecondGroupObservations": [
1,
3
]
},
"output": {
"result": {
"value": 0.25
}
}
}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 Common Language Effect Size Calculator for a complementary operation: Common-language effect size summarizes cross-group pairwise superiority.
Use Hedges g From t Statistic Converter for a complementary operation: Hedges' g adjusts an independent-group standardized contrast for sample-size bias.
References
-
Cliff Delta Nonoverlap Calculator — tool.io
Similar or alternative tools
- Common Language Effect Size Calculator
Common-language effect size summarizes cross-group pairwise superiority.
- Hedges g From t Statistic Converter
Hedges' g adjusts an independent-group standardized contrast for sample-size bias.