Description
Count distinct people in selectedWave and its observed subset, dividing or returning zero with defined false when no eligible people remain.
Longitudinal ageing research links observations to people, waves, and sources. A person may appear in multiple records, so distinct-person coverage and record counts answer different questions and require explicit duplicate rules.
Count distinct people in selectedWave and its observed subset, dividing or returning zero with defined false when no eligible people remain.
When to use this tool
Use Aging Panel Wave Support Share when you need a record-coverage or source-support diagnostic in ageing research.
How to use the tool and how it works
- Enter personIds, waveIds, observed, selectedWave. Keep parallel arrays aligned. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read eligiblePeople, observedPeople, share, defined. Inspect defined before interpreting the associated values.
Require aligned personIds, waveIds, and observed flags. Count distinct people in selectedWave and its observed subset, dividing or returning zero with defined false when no eligible people remain.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| personIds | Person Ids | Required. Array of text; maximum UTF-16 length 8192; maximum items 256. |
| waveIds | Wave Ids | Required. Array of text; maximum UTF-16 length 8192; maximum items 256. |
| observed | Observed | Required. Array of boolean; maximum items 256. |
| selectedWave | Selected Wave | Required. Text; maximum UTF-16 length 8192. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| eligiblePeople | Eligible People | Required. Safe integer. |
| observedPeople | Observed People | Required. Safe integer. |
| share | Dimensionless share on the numerator and denominator basis stated above. | Required. Finite number. |
| defined | Whether the stated denominator or normalization exists; inspect before interpreting a zero placeholder. | Required. Boolean. |
{
"input": {
"personIds": [
"p1",
"p1",
"p2"
],
"waveIds": [
"1",
"1",
"1"
],
"observed": [
true,
false,
false
],
"selectedWave": "1"
},
"output": {
"eligiblePeople": 2,
"observedPeople": 1,
"share": 0.5,
"defined": true
}
}Limitations and assumptions
- One observed duplicate row supports the person despite other missing rows; identity, actual response, representative follow-up, and selection bias are not assessed.
- Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
Alternative or Complementary methods
Review the original study design, identifiers, and missing-data definitions. Use the full longitudinal dataset for inference rather than treating a local coverage flag as evidence of representativeness.
References
Similar or alternative tools
- Aging Cohort Selective Attrition Share
Return each retention rate, their difference, and retained-group share among all retained.
- Proxy Wave Transition Token
Compare them literally and serialize the ordered pair as transitionKey.