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Correcting False Positive Rates in Interaction Model Testing

This corrigendum addresses errors and limitations discovered after the publication of Esarey and Sumner's paper on interaction models.

Correction Overview:

The authors recognized significant issues with their previous work, particularly concerning the overconfidence of the Brambor et al. procedure for separately testing multiple hypotheses.

  • The original paper correctly identified this limitation.
  • This corrigendum details these errors and introduces a new robust procedure to address them.

Understanding the Problem:

The authors uncovered these issues while developing methods for another unrelated paper, highlighting potential pitfalls in applying established procedures.

  • The Brambor et al. procedure may be overly optimistic when testing hypotheses individually.
  • Its application is appropriate but limited when testing multiple hypotheses simultaneously.

The Solution:

This update provides a comprehensive description of the limitations related to the Benjamini and Hochberg method for separate hypothesis testing (which was presented in their paper).

  • The authors suggest a procedure on pp. 1161–1163 based on this methodology.
  • This corrigendum introduces an improved, more robust approach developed during this process.

Revised InteractionTest Software:

The article includes updated methods designed to better handle false positives in interaction model analyses.

Comparative Political Studies
Marginal Effects in Interaction Models: Determining and Controlling the False Positive Rate (Corrigendum) was authored by Justin Esarey and Jane Lawrence Sumner. It was published in CPS in 2021. Find on Google Scholar10.1177/0010414020970212
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