ArticleAdvances in methods and practices in psychological science
When Do Interaction/Moderation Effects Stabilize in Linear Regression?
Article in Advances in methods and practices in psychological science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- The Relationship Between Psychopathy and Violence: A Comparison Across Birth Cohorts.International journal of forensic mental health · 2026Article
- Visual search advantages in tactical decision-making of male soccer players: evidence from 3V2 and 3V3 scenarios.Frontiers in psychology · 2026Article
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Authors and funding
5 authors.
Funding
Abstract
Two-way interaction effects in linear regression occur when the relation between two variables changes depending on the level of a third. Despite their frequent use, interactions are notoriously difficult to estimate accurately and test for statistical significance because of small effect sizes and low reliability. In this study, we used Monte Carlo simulations to establish stability thresholds for two-way interactions between continuous variables across combinations of reliability (0.7-1.0), main effect size (0.1-0.5), collinearity (0.1-0.5), and interaction effect size (0.05-0.2). Stability was defined as the consistency of estimated effect sizes across repeated samples of the same size from the same population and operationalized using modified definitions of the corridor of stability and point of stability from Schönbrodt and Perugini. Results show that the stability of interaction estimates is primarily determined by sample size and predictor reliability. The case representing a realistic psychology field study, in which researchers have limited control over variables, stabilized at
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