Mediation Indirect Effect a*b Calculator
Algebraic independently fit linear mediationindirecteffecta×b, compatible scaling. Not causal mediation identification, bootstrap uncertainty or claim of significance. Actual independently qualified instrument/cohort/matching units; no diagnosis, causal outcome, validated personal prediction or universal clinical cutoff.
Description
A linear mediation product multiplies two compatible path coefficients.
A linear mediation product multiplies two compatible path coefficients.1
Causal interpretation and uncertainty require information beyond that multiplication. The calculation and input requirements are explained below.
When to use Mediation Indirect Effect a*b Calculator
Enter finite matched path coefficients a and b.
How to use Mediation Indirect Effect a*b 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 Mediation Indirect Effect a*b 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 |
|---|---|---|---|
| actualPathA | Actual Path A. Use the units and matching context stated in the calculation below. | number | Required; finite; other constraints below |
| actualPathB | Actual Path B. Use the units and matching context stated in the calculation below. | number | Required; finite; other constraints below |
Enter finite matched path coefficients a and b. Multiply and return their signed product. No confidence interval, significance test or causal identification is performed.
indirectEffect=a*b 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": {
"actualPathA": 2,
"actualPathB": 3
},
"output": {
"result": {
"value": 6
}
}
}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 Sobel Test Z Mediation Calculator for a complementary operation: The Sobel statistic uses a first-order variance approximation for a product of paths.
Use Simple Slope at +/-1 SD Calculator for a complementary operation: A linear interaction model has a predictor slope that depends on moderator value.
References
-
Mediation Indirect Effect a*b Calculator — tool.io
Similar or alternative tools
- Sobel Test Z Mediation Calculator
The Sobel statistic uses a first-order variance approximation for a product of paths.
- Simple Slope at +/-1 SD Calculator
A linear interaction model has a predictor slope that depends on moderator value.