Institutional Trust Composite Z Calculator
Weighted mean of three independently established signed institution-trust z-scores and caller nonnegative weights. The historical output name knownWeightedScore denotes the weighted z-score, not a 0–100 grade. Each score requires a verified compatible reference population, direction and calibration; missing evidence/weight remains explicit. A weighted mean of z-scores is not automatically unit-variance: covariance/restandardization and survey interpretation remain external.
Description
An institutional-trust z composite uses independently standardized signed indicators.
An institutional-trust z composite uses independently standardized signed indicators.1
Its weights, reference population and missing-evidence coverage determine the resulting weighted score.
When to use Institutional Trust Composite Z Calculator
Use this tool to obtain knownWeightedScore, unknownWeightFraction, unknownCriterionIndices from the supplied records using the stated calculation. Establish the population, period, variable definitions, sample coverage and independently applicable instrument or calibration.
How to use Institutional Trust Composite Z Calculator and understand its results
- Establish the population, period, variable definitions, sample coverage and independently applicable instrument or calibration.
- Enter independentlyAnnotatedCriterionScores, callerCalibratedCriterionWeights, criterionKnownFlags, using the field meanings and rules below, then run the tool.
- Read knownWeightedScore with unknownWeightFraction and unknownCriterionIndices. A score over known domains does not fill missing evidence.
- Correct any reported input issue and run again. Before using a successful result, check the stated units, signs, reference scope and observation coverage.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| independentlyAnnotatedCriterionScores | Independently annotated criterion scores | list of number | Required |
| callerCalibratedCriterionWeights | Caller calibrated criterion weights | list of number | Required |
| criterionKnownFlags | Criterion known flags; binary 1 means the matched observation is known, 0 means unknown | list of number | Required |
Supply exactly 3 aligned independently calibrated domain scores, nonnegative weights and binary known flags. Signed finite standardized scores are accepted. Both total weight and weight attached to known domains must be positive. Average known scores using known weights only; separately return the unknown share of total weight and zero-based unknown indices. Unknown domains are not imputed.
knownWeightedScore=Σ(score_i×weight_i×known_i)/Σ(weight_i×known_i); unknownWeightFraction=Σ(weight_i×(1−known_i))/Σweight_i Use the matching field units and the exact boundary, ordering and reference rules above.
| Output field | Meaning | Value type |
|---|---|---|
| result | Calculated observation or qualified reference | object |
| result.knownWeightedScore | Weighted mean over known domains only, normalized by their known weight. | number |
| result.unknownWeightFraction | Weight attached to unknown domains divided by total declared weight; fraction, not percent. | number |
| result.unknownCriterionIndices | Zero-based domains whose supplied evidence is marked unknown. | list |
{
"input": {
"independentlyAnnotatedCriterionScores": [
20,
40,
60
],
"callerCalibratedCriterionWeights": [
1,
2,
1
],
"criterionKnownFlags": [
1,
1,
1
]
},
"output": {
"result": {
"knownWeightedScore": 40,
"unknownWeightFraction": 0,
"unknownCriterionIndices": []
}
}
}Limitations and assumptions
Population definitions, survey design, calibration and observation coverage are independently established. A result describes the supplied record or conditional model without demonstrating causation, validating an instrument or supplying representative population evidence.
Missing required fields, unknown fields, wrong types and violated rules return input issues. Numeric values and outputs must be finite. Lists and matrices must be dense, without missing cells. Numeric lists allow at most 10000 entries, subject to the narrower lengths and code rules above. Extremely large composite outputs are rejected.
Alternative or Complementary methods
For a related step, use Generalized Trust Share Percent Calculator: A generalized-trust share summarizes responses under an adopted survey question and coding. For a complementary comparison, use Putnam Regional Social Capital Index Calculator: A regional social-capital composite requires declared indicators, calibration and sampling context.
References
Similar or alternative tools
- Generalized Trust Share Percent Calculator
A generalized-trust share summarizes responses under an adopted survey question and coding.
- Putnam Regional Social Capital Index Calculator
A regional social-capital composite requires declared indicators, calibration and sampling context.