Construct · 1 fields · 1 citations

Freedman's paradox: a standalone construct

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Statistics

variables screened for significance and then refitted look strongly predictive even when all are pure noise.

In statistics, Freedman's paradox refers to variables screened for significance and then refitted look strongly predictive even when all are pure noise. This meaning comes from Freedman (1983) in The American Statistician.[1]

Unit
Recovery means
Measured by

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Nearby constructs

noise4 fields · 5 citationsjingle · one word, four constructs paradox3 fields · 4 citationsjingle · one word, three constructs significance4 fields · 4 citationsjingle · one word, four constructs

References

Freedman, D. A. (1983). A Note on Screening Regression Equations. The American Statistician, 37(2), 152-155. https://doi.org/10.1080/00031305.1983.10482729

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