To interact or not to interact: The pros and cons of including interactions in linear regression models
Aljoscha Rimpler; Henk A. L. Kiers; Don van Ravenzwaaij · 2025 · Behavior Research Methods
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Interaction effects are very common in the psychological literature. However, interaction effects are typically very small and often fail to replicate. In this study, we conducted a simulation comparing the generalizability and estimability of two linear regression models: one correctly specified to account for interaction effects and one misspecified including simple effects only. We manipulated noise levels, predictor variable correlations, and different sets of regression weights, resulting in 9216 different conditions. From each dataset, we drew 1000 samples of N = 25, 50, 100, 250, 500, a
Abstract by Aljoscha Rimpler; Henk A. L. Kiers; Don van Ravenzwaaij, Behavior Research Methods (2025) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.3758/s13428-025-02613-6