Applied Linear Statistical Models¶
Kutner, M. H. (2005). Applied Linear Statistical Models. McGraw-Hill.
Cited by¶
1 citation across 1 artifact.
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Domain-specific¶
- Collinearity Inflation
- Since a coefficient's standard error scales with √VIF, each of these two coefficients is estimated with about √10.3 ≈ 3.2 times the standard error it would have if the predictors were uncorrelated
This sourceThe variance inflation factor as the formal collinearity diagnostic, with the maximum-VIF-in-excess-of-10 rule of thumb. The textbook identity that a coefficient's sampling variance equals its zero-correlation variance multiplied by the variance inflation factor.
Supported in partVerified against the work's full text
“highly useful formal diagnostic, the [variance inflation factor]. Informal Diagnostics Example Indications”
- Since a coefficient's standard error scales with √VIF, each of these two coefficients is estimated with about √10.3 ≈ 3.2 times the standard error it would have if the predictors were uncorrelated
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