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Does Raising Type 1 Error Rate Improve Power to Detect Interactions in Linear Regression Models? A Simulation Study

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  • Casey P Durand

Abstract

Introduction: Statistical interactions are a common component of data analysis across a broad range of scientific disciplines. However, the statistical power to detect interactions is often undesirably low. One solution is to elevate the Type 1 error rate so that important interactions are not missed in a low power situation. To date, no study has quantified the effects of this practice on power in a linear regression model. Methods: A Monte Carlo simulation study was performed. A continuous dependent variable was specified, along with three types of interactions: continuous variable by continuous variable; continuous by dichotomous; and dichotomous by dichotomous. For each of the three scenarios, the interaction effect sizes, sample sizes, and Type 1 error rate were varied, resulting in a total of 240 unique simulations. Results: In general, power to detect the interaction effect was either so low or so high at α = 0.05 that raising the Type 1 error rate only served to increase the probability of including a spurious interaction in the model. A small number of scenarios were identified in which an elevated Type 1 error rate may be justified. Conclusions: Routinely elevating Type 1 error rate when testing interaction effects is not an advisable practice. Researchers are best served by positing interaction effects a priori and accounting for them when conducting sample size calculations.

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  • Casey P Durand, 2013. "Does Raising Type 1 Error Rate Improve Power to Detect Interactions in Linear Regression Models? A Simulation Study," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-5, August.
  • Handle: RePEc:plo:pone00:0071079
    DOI: 10.1371/journal.pone.0071079
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    1. Yoshinori Nakagawa, 2016. "Effect of critical thinking disposition on household earthquake preparedness," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(2), pages 807-828, March.
    2. Thuy‐Van Tran & Janne Järvinen, 2022. "Understanding the concept of subjectivity in performance evaluation and its effects on perceived procedural justice across contexts," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(3), pages 4079-4108, September.
    3. Luetke, Maya & Judge, Ashley & Kianersi, Sina & Jules, Reginal & Rosenberg, Molly, 2020. "Hurricane impact associated with transactional sex and moderated, but not mediated, by economic factors in Okay, Haiti," Social Science & Medicine, Elsevier, vol. 261(C).
    4. Elina Bryngemark & Patrik Söderholm, 2022. "Green industrial policies and domestic production of biofuels: an econometric analysis of OECD countries," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 24(2), pages 225-261, April.
    5. Yoshinori Nakagawa, 2016. "Effect of critical thinking disposition on household earthquake preparedness," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(2), pages 807-828, March.

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