Description
Calculate one logit probability-derivative term and its averaging contribution.
Econometric calculations separate supplied residuals, regressors, weights, restrictions, panel groups and reference periods. One score or moment contribution is not a fitted estimator, and one scalar covariance term is not a standard error. Unit rescaling and event-time arithmetic preserve conventions without establishing model identification or causal interpretation.
Calculate one logit probability-derivative term and its averaging contribution.
When to use this tool
Use Logit Average Partial Effect Row when you already have coefficient, predictedProbability, averagingCount and need to calculate one logit probability-derivative term and its averaging contribution.
How to use the tool and how it works
- Enter coefficient, predictedProbability, averagingCount. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read rowPartialEffect, averageContribution. Use the output convention below.
Require supplied probability in [0,1] and positive safe averagingCount; row=coefficient*p*(1-p), contribution=row/count.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| coefficient | Coefficient | Required. Finite number. |
| predictedProbability | Predicted Probability | Required. Finite number; minimum 0; maximum 1. |
| averagingCount | Averaging Count | Required. Safe integer; minimum 1. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| rowPartialEffect | coefficient*p*(1-p), a local continuous-predictor derivative under the supplied model. | Required. Finite number. |
| averageContribution | One rowPartialEffect/averagingCount term, not the complete average. | Required. Finite number. |
{
"input": {
"coefficient": 2,
"predictedProbability": 0.5,
"averagingCount": 100
},
"output": {
"rowPartialEffect": 0.5,
"averageContribution": 0.005
}
}Limitations and assumptions
- This is a local continuous-predictor derivative under the stated coefficient convention, not a fitted logit, discrete-change effect or complete average partial effect. Interactions require their own derivative.
- 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
Fit and evaluate the full specified model with appropriate data, grouping and uncertainty treatment for inference. Aggregate the required score/moment terms and use the complete covariance calculation; a local residual, cutoff flag or supplied coefficient transformation does not validate the estimator.
References
Similar or alternative tools
- Log Linear Coefficient Percent Crosswalk
Convert a supplied log-linear coefficient change to a model-implied multiplicative and percentage change.
- Weighted Regression Single Score Term
Calculate one weighted regression score contribution.