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Equivalence testing for linear regression.

Harlan Campbell1

  • 1Department of Statistics, University of British Columbia.

Psychological Methods
|November 13, 2023
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Summary
This summary is machine-generated.

This study introduces new equivalence testing methods for linear regression to confirm no meaningful association between variables. These tests are valuable for establishing the absence of a relationship in statistical analyses.

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Area of Science:

  • Statistics
  • Psychometrics
  • Quantitative Psychology

Background:

  • Equivalence testing is crucial for demonstrating the absence of a meaningful effect.
  • Traditional null hypothesis significance testing is often insufficient for confirming no association.

Conclusions:

  • The proposed equivalence tests offer a robust framework for confirming the absence of meaningful associations in regression.
  • These methods enhance the ability of researchers to definitively conclude no relationship exists.
  • The study facilitates a more comprehensive understanding of statistical inference in regression analysis.