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May 21, 2026Stats0 citationsOpen Access

Defining Effect Size Thresholds for OR, RR, and η² in Physiotherapy Studies

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GZGrzegorz Zieliński

Key Points

  • The aim is to establish physiotherapy-specific reference values for effect size metrics like odds ratio and relative risk.
  • Cohen’s d values were transformed into odds ratios, relative risks, and η² using algebraic relationships.
  • Calculations utilized baseline risks of 0.1, 0.2, and 0.5 while assuming equal group sizes and homogeneity of variances.
  • Analyses were performed using R 4.3.1 software.
  • Odds ratio thresholds identified as 1.20 (small), 2.07 (medium), and 4.27 (large).
  • For relative risk at p0 = 0.1, thresholds were 1.18, 1.95, and 3.22; at p0 = 0.5, they were 1.09, 1.35, and 1.62.
  • Corresponding η² values were found to be 0.003, 0.039, and 0.138.

Abstract

(1) Background: Effect size interpretation in physiotherapy research varies across statistical models, hindering comparability between studies using linear, logistic, and variance-based analyses. Unified, discipline-specific thresholds are needed to harmonise interpretation and support consistent sample size planning in clinical trials. The aim is to estimate physiotherapy-specific reference values for odds ratio (OR), relative risk (RR), and η2/ηp2 based on empirically established thresholds for Cohen’s d (0.1, 0.4, and 0.8). (2) Methods: Cohen’s d values were transformed into corresponding effect size metrics using deterministic algebraic relationships. Specifically, OR, RR, and η2 were derived from Cohen’s d under selected baseline risks (p0 = 0.1, 0.2, and 0.5). Calculations were performed in R 4.3.1 assuming equal group sizes and homogeneity of variances. (3) Results: OR thresholds were 1.20 (small), 2.07 (medium), and 4.27 (large). For RR, at p0 = 0.1, thresholds were 1.18, 1.95, and 3.22; at p0 = 0.5, they were 1.09, 1.35, and 1.62. Corresponding η2/ηp2 values were 0.003, 0.039, and 0.138. (4) Conclusions: The derived thresholds form a coherent, numerically anchored framework linking linear, logistic, and variance-based effect sizes. This approach standardises interpretation across statistical models and strengthens methodological consistency in physiotherapy clinical research.

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Cite This Study

Grzegorz Zieliński (2026) studied this question.

synapsesocial.com/papers/6a0ea127be05d6e3efb5f941https://doi.org/10.3390/stats9030049
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