An empirically based power primer for laboratory aggression research

Abstract

Recent reviews suggest that, like much of the psychological literature, research studies using laboratory aggression paradigms tend to be underpowered to reliably locate commonly observed effect sizes (e.g., r = ~.10–.20, Cohen's d = ~0.20–0.40). In an effort to counter this trend, we provide a “power primer” that laboratory aggression researchers can use as a resource when planning studies using this methodology. Using simulation‐based power analyses and effect size estimates derived from recent literature reviews, we provide sample size recommendations based on type of research question (e.g., main effect vs. two‐way vs. three‐way interactions) and correlations among predictors. Results highlight the large number of participants that must be recruited to reach acceptable (~80%) power, especially for tests of interactions where the recommended sample sizes far exceed those typically employed in this literature. These discrepancies are so substantial that we urge laboratory aggression researchers to consider a moratorium on tests of three‐way interactions. Although our results use estimates from the laboratory aggression literature, we believe they are generalizable to other lines of research using behavioral tasks, as well as psychological science more broadly. We close by offering a series of best practice recommendations and reiterating long‐standing calls for attention to statistical power as a basic element of study planning.

Interactive Effects of Mindfulness and Negative Urgency on Intimate Partner Aggression Perpetration

“…The studies were quite similar, the samples were drawn from the same population in consecutive academic years, and the self-report measures have demonstrated utility in both virtual and in-lab administration. Importantly, it has become increasingly apparent that betweenparticipant interactions, such as those we model here, require far more statistical power than researchers, such as us, previously thought (e.g., Hyatt et al, 2022)…”

“…Additionally, the results of Study 2 are likely underpowered to detect substantial moderating effects of the audio induction. Future investigations should utilize larger samples to ensure adequate power based on a priori power analysis (Hyatt et al, 2022).…”

Interactive effects of mindfulness and negative urgency on intimate partner aggression perpetration

“…The studies were quite similar, the samples were drawn from the same population in consecutive academic years, and the self-report measures have demonstrated utility in both virtual and in-lab administration. Importantly, it has become increasingly apparent that between-participant interactions, such as those we model here, require far more statistical power than researchers, such as us, previously thought (e.g., Hyatt et al, 2022) 2. Notably, the final sample of participants consisted of a majority of non-White undergraduate students, which is representative of the larger undergraduate population at the university.…”

“…Similarly, Study 2 included a brief audio induction, which may not Additionally, the results of Study 2 are likely underpowered to detect substantial moderating effects of the audio induction. Future investigations should utilize larger samples to ensure adequate power based on a priori power analysis (Hyatt et al, 2022).…”

Moderation effects in personality disorder research.

“…Though we have focused on psychopathy trait-by-trait interactions, many of the difficulties in detecting these interactions generalize to other personality disorder research scenarios. For example, Hyatt et al (2021) examined power to detect interactions in laboratory aggression research, where researchers frequently examine how experimental condition, a factor with reliability of 1.0, moderates the impact of personality pathology on aggression (Vize et al, 2021; West et al, 2021). Hyatt et al (2021) found that even with interaction effect sizes that are double the size of those typically found in the literature, adequate power (.80) would require sample sizes of at least N = 1,000.…”