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Regression dilution

Regression dilution, also known as regression attenuation, is the biasing of the linear regression slope towards zero (the underestimation of its absolute value), caused by errors in the independent variable.

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Overview

Slope correction

Correlation correction

Applicability

Advanced semantic analysis

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Map overview Semantic statistics

Regression dilution

Nodes49
Edges48
Triples27
Avg. degree1.96
Density0.040816
Components1

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Regression dilution

Top relations

related to Applicability · 10
Regression dilution → Because, Frost, However, In, Let, Regression, Standard, There, Thompson, To
related to The case of a randomly distributed x variable · 7
Regression dilution → For, Frost, Fuller, Longford, The, Thompson, Under
related to Further reading · 5
Regression dilution → Frost, Regression, Spearman, Thompson, Those
related to Correlation correction · 4
Regression dilution → Charles Spearman, In, Pearson, The

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Important terminology

regression variable slope measurement correlation estimated dilution correction bias noise ratio variability error example estimate displaystyle true variables also models

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
blood pressure may be viewed as arising from a random sample.Under certain assumptionsinstance ofand their characteristics0.80text
Regression dilutionrelated to ApplicabilityHowever0.60section
Regression dilutionrelated to ApplicabilityIn0.60section
Regression dilutionrelated to ApplicabilityTo0.60section
Regression dilutionrelated to ApplicabilityLet0.60section
Regression dilutionrelated to ApplicabilityFrost0.60section
Regression dilutionrelated to ApplicabilityThompson0.60section
Regression dilutionrelated to ApplicabilityRegression0.60section
Regression dilutionrelated to ApplicabilityBecause0.60section
Regression dilutionrelated to ApplicabilityStandard0.60section
Regression dilutionrelated to ApplicabilityThere0.60section
Regression dilutionrelated to Correlation correctionCharles Spearman0.60section

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