Rasch Person Separation Index Calculator
Rasch person separation G=sqrt((observed variance−meanSE²)/meanSE²), actual same calibration logits; negative adjusted variance refused, no diagnosis or universal strata. Actual independently qualified instrument/cohort/matching units; no diagnosis, causal outcome, validated personal prediction or universal clinical cutoff.
Description
Rasch person separation compares estimated true variance with measurement-error variance.
Rasch person separation compares estimated true variance with measurement-error variance.1
The observed variance and error variance must come from the same calibration scale. The calculation and input requirements are explained below.
When to use Rasch Person Separation Index Calculator
Enter nonnegative observed person-measure variance and positive mean squared measurement error.
How to use Rasch Person Separation 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 Rasch Person Separation 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 |
|---|---|---|---|
| actualObservedPersonMeasureVariance | Actual Observed Person Measure Variance. Use the units and matching context stated in the calculation below. | number | Required; nonnegative; finite; other constraints below |
| callerMeanSquaredMeasurementError | Caller Mean Squared Measurement Error. Use the units and matching context stated in the calculation below. | number | Required; strictly positive; finite; other constraints below |
Enter nonnegative observed person-measure variance and positive mean squared measurement error. Observed variance must be at least error variance. Return the square root of their difference divided by error variance; equality yields zero separation.
separation=sqrt((observedVariance-errorVariance)/errorVariance) 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": {
"actualObservedPersonMeasureVariance": 5,
"callerMeanSquaredMeasurementError": 1
},
"output": {
"result": {
"value": 2
}
}
}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 Wright Map Item Position Lookup for a complementary operation: A Wright map places person measures and item locations on a common calibrated scale.
Use Rasch Item Difficulty Logits Calculator for a complementary operation: A restricted Rasch difficulty estimate transforms an observed correct-response fraction into logits.
References
-
Rasch Person Separation Index Calculator — tool.io
Similar or alternative tools
- Wright Map Item Position Lookup
A Wright map places person measures and item locations on a common calibrated scale.
- Rasch Item Difficulty Logits Calculator
A restricted Rasch difficulty estimate transforms an observed correct-response fraction into logits.