Description
effect = coefficient*probability*(1-probability).
Regression model terms depend on the response link, variable scale and the meaning of coefficients. A local marginal effect, elasticity or model mean computed from supplied parameters does not estimate those parameters or establish causality.
effect = coefficient*probability*(1-probability).
When to use this tool
Use Logit Marginal Effect One Covariate when checking one stated regression-model contribution.
How to use the tool and how it works
- Enter probability, coefficient. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read effect. Use the output convention below.
Require probability in [0,1]. effect = coefficient*probability*(1-probability).1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| probability | Dimensionless probability from zero to one under the stated model. | Required. Finite number; minimum 0; maximum 1. |
| coefficient | Coefficient | Required. Finite number. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| effect | Effect | Required. Finite number. |
{
"input": {
"probability": 0.5,
"coefficient": 2
},
"output": {
"effect": 0.5
}
}Limitations and assumptions
- This is a continuous-covariate derivative for a simple logit index. It is not a discrete indicator contrast, an average marginal effect or a coefficient estimate.
- 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.
- Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.
Alternative or Complementary methods
Use a fitted model, suitable data and defensible identification for prediction, inference and causal interpretation.
References
Similar or alternative tools
- Measurement Error Attenuation Factor Term
reliability = signalVariance/sum; expectedSlope = trueSlope*reliability.
- Omitted Variable Bias Supplied Covariance Term
bias = omittedEffect*covariance/includedVariance.