An effect size distribution analysis of heart rate variability studies: Recommendations for reporting the magnitude of group differences

The calculation of heart rate variability (HRV) is a popular tool used to investigate differences in cardiac autonomic control between population samples. When interpreting effect sizes to quantify the magnitude of group differences, researchers typically use Cohen's guidelines of small (0.2), medium (0.5), and large (0.8) effects. However, these guidelines were only proposed for use when the effect size distribution (ESD) was unknown. Despite the availability of effect sizes from hundreds of HRV studies, researchers still largely rely on Cohen's guidelines to interpret effect sizes. This article describes an ESD analysis of 297 HRV effect sizes from case-control studies, revealing that the 25th, 50th, and 75th effect size percentiles correspond with effect sizes of 0.25, 0.5, and 0.84, respectively. The ESD for separate clinical groups are also presented. The data suggests that Cohen's guidelines underestimate the magnitude of small and large effect sizes for the body of HRV case-control research. Therefore, to better reflect observed HRV effect sizes, the data suggest that effect sizes of 0.25, 0.5, and 0.85 should be interpreted as small, medium, and large effects. Researchers are encouraged to use the ESD dataset or their own collected datasets in tandem with the provided analysis script to perform bespoke ESD analyses relevant to their specific research area.