Description
reliability = signalVariance/sum; expectedSlope = trueSlope*reliability.
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.
reliability = signalVariance/sum; expectedSlope = trueSlope*reliability.
When to use this tool
Use Measurement Error Attenuation Factor Term when checking one stated regression-model contribution.
How to use the tool and how it works
- Enter signalVariance, errorVariance, trueSlope. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read reliability, expectedSlope. Use the output convention below.
Require nonnegative signalVariance and errorVariance with positive sum. reliability = signalVariance/sum; expectedSlope = trueSlope*reliability.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| signalVariance | Signal Variance | Required. Finite number; minimum 0. |
| errorVariance | Error Variance | Required. Finite number; minimum 0. |
| trueSlope | True Slope | Required. Finite number. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| reliability | Reliability | Required. Finite number. |
| expectedSlope | Expected Slope | Required. Finite number. |
{
"input": {
"signalVariance": 4,
"errorVariance": 1,
"trueSlope": 2
},
"output": {
"reliability": 0.8,
"expectedSlope": 1.6
}
}Limitations and assumptions
- The attenuation interpretation assumes classical additive measurement error under the relevant regression conditions. Variances are supplied, not estimated; correlated or outcome measurement error needs other models.
- 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
- Logit Marginal Effect One Covariate
effect = coefficient*probability*(1-probability).
- Omitted Variable Bias Supplied Covariance Term
bias = omittedEffect*covariance/includedVariance.