Delphi Consensus
Measure real-time Delphi consensus from expert ratings.
Description
Delphi consensus screening compares the range and population dispersion of supplied expert ratings.
Delphi consensus screening compares the range and population dispersion of supplied expert ratings. Both caller-selected tolerances must pass.1
Measure real-time Delphi consensus from expert ratings.
When to use Delphi Consensus
Use this tool to measure real-time Delphi consensus from expert ratings.
Prepare the recorded observations, ratings, assumptions or expected/observed lists requested. Choose thresholds and definitions appropriate to the planning question.
How to use Delphi Consensus and understand its results
- Prepare the recorded observations, ratings, assumptions or expected/observed lists requested. Choose thresholds and definitions appropriate to the planning question.
- Enter expertRatings, consensusRangeThreshold, consensusStdDevThreshold using the field table and calculation rules, then run the tool.
- Read meanRating, ratingRange, populationStdDev, consensusReached. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| expertRatings | Expert ratings | list of number | Required |
| consensusRangeThreshold | Maximum rating range | number; minimum: 0 | Required |
| consensusStdDevThreshold | Maximum standard deviation | number; minimum: 0 | Required |
Enter at least two finite signed ratings and nonnegative range/SD thresholds. Return mean, range, population SD and inclusive gate.
SD=√(Σ(rating−mean)²/n); consensus=range≤limit AND SD≤limit Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| meanRating | Mean rating | number |
| ratingRange | Rating range | number; minimum: 0 |
| populationStdDev | Population standard deviation | number; minimum: 0 |
| consensusReached | Consensus meets supplied thresholds | boolean |
{
"input": {
"expertRatings": [
4,
4,
5,
5
],
"consensusRangeThreshold": 1,
"consensusStdDevThreshold": 0.5
},
"output": {
"meanRating": 4.5,
"ratingRange": 1,
"populationStdDev": 0.5,
"consensusReached": true
}
}Limitations and assumptions
No expert solicitation, iterative feedback, representativeness or validated consensus standard is supplied.
Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors. A successfully returned false flag is an evaluated outcome; its meaning is explained above.
Alternative or Complementary methods
Use Forecast Calibration: Calculate Brier score and calibration gap for binary forecasts. For a complementary task, use Wildcard Triage: Score wildcard confidence, plausibility, and impact for triage.
References
-
Delphi Consensus — tool.io
Similar or alternative tools
- Forecast Calibration
Calculate Brier score and calibration gap for binary forecasts.
- Wildcard Triage
Score wildcard confidence, plausibility, and impact for triage.