Duncan Segregation Index Calculator
Observed occupation-unitDuncan dissimilarity from independently assigned aggregate two group counts, not the Duncan SEI or individual identity/group membership prediction.
Description
Occupational dissimilarity compares two groups across the same occupational units.
Occupational dissimilarity compares two groups across the same occupational units.1
This distributional index differs from an occupational socioeconomic-status score. The calculation and input requirements are explained below.
When to use Duncan Segregation Index Calculator
Enter aligned nonnegative integer counts up to 1000000 for two groups across the same units.
How to use Duncan Segregation Index 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 Duncan Segregation Index 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 |
|---|---|---|---|
| actualFirstGroupCountsByUnit | Actual First Group Counts By Unit. Use the units and matching context stated in the calculation below. | array of number | Required; other constraints below |
| actualSecondGroupCountsByUnit | Actual Second Group Counts By Unit. Use the units and matching context stated in the calculation below. | array of number | Required; other constraints below |
Enter aligned nonnegative integer counts up to 1000000 for two groups across the same units. Require both group totals positive. Sum absolute differences between each unit's two normalized group shares and halve the sum. Unit boundaries and group assignments are supplied externally.
dissimilarity=0.5*sum(abs(xi/sum(x)-yi/sum(y))) 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.observedDissimilarity | Observed Dissimilarity. Interpret its unit, sign, order or availability flag as explained above. | number |
{
"input": {
"actualFirstGroupCountsByUnit": [
8,
2
],
"actualSecondGroupCountsByUnit": [
2,
8
]
},
"output": {
"result": {
"observedDissimilarity": 0.6000000000000001
}
}
}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 Isolation Segregation Index Calculator for a complementary operation: Isolation measures how much members of one group share local areas with their own group.
Use Exposure Segregation Index Calculator for a complementary operation: Exposure measures how much members of one group share local areas with another group.
References
-
Duncan Segregation Index Calculator — tool.io
Similar or alternative tools
- Isolation Segregation Index Calculator
Isolation measures how much members of one group share local areas with their own group.
- Exposure Segregation Index Calculator
Exposure measures how much members of one group share local areas with another group.