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How Big is a Big Odds Ratio? Interpreting the Magnitudes of Odds Ratios in Epidemiological Studies
Abstract
The odds ratio (OR) is probably the most widely used index of effect size in epidemiological studies. The difficulty of interpreting the OR has troubled many clinical researchers and epidemiologists for a long time. We propose a new method for interpreting the size of the OR by relating it to differences in a normal standard deviate. Our calculations indicate that OR = 1.68, 3.47, and 6.71 are equivalent to Cohen's d = 0.2 (small), 0.5 (medium), and 0.8 (large), respectively, when disease rate is 1% in the nonexposed group; Cohen's d < 0.2 when OR <1.5, and Cohen's d > 0.8 when OR > 5.
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“Although the effect sizes of Hedges g and OR can be difficult to compare, outcomes based on continuous data and reported as Hedges g, appeared to generate larger effect sizes compared with dichotomous scoring, reported as OR [91].”
From The psychological subtype of intimate partner violence and its effect on mental health: a systematic review with meta-analyses (2022) · cites this paper as [91]
In the citing paper
“The mentoring structures and outcomes of the students in our study differed based on their gender and race/ethnicity, although the sizes of these differences were small (Cohen, 1992; Chen et al., 2010).”
From Race and Gender Differences in Undergraduate Research Mentoring Structures and Research Outcomes (2017) · cites this paper as Chen et al., 2010
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“This odds ratio is considered to be a small to medium effect size [38].”
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“0 medium, and those greater than 5 large effects.(28) Our aim in choosing the cutoff value was to avoid even small decrease in seizure quality, that is, to ensure that ORs remain less than 1.”
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“Following previously established reference values, an OR below 1.5 was considered weak and above 5.0 strong [66].”
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“1, small effect size) to a set of a-priori defined network templates provided by GIFT (Chen et al., 2010; Li et al., 2017; Shi et al., 2018; Ye et al., 2014).”
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“Odds ratios smaller than 1.5 can be considered as small effect size and larger than 1.5 as moderate or large effect size (Chen, Cohen, & Chen, 2010).”
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“Using the most conservative suggestion proposed by Chen et al. we interpret OR of 1.68, 3.47 and 6.71 to be equivalent to Cohen’s d of 0.2 (small), 0.5 (medium), and 0.8 (large), respectively (Chen et al., 2010).”
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“The effect size was estimated using Chen et al. 2010 [42]; small effect size: OR < 1.6, medium effect size: OR > 1.5|OR < 5, large effect size: OR > 5.”
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“The OR values of 1.68, 3.47, and 6.71 correspond to Cohen’s d of 0.2 (small), 0.5 (medium), and 0.8 (large) effect sizes, respectively (see Chen et al., 2010).”
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“The OR size corresponds to a small effect [38].”
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“Those between 3.47 and 6.70 are considered moderate, and those of 6.71+ are considered large (Chen et al., 2010).”
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“, 2019), equivalent to a large Cohen's d effect size (Chen et al., 2010).”
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“Again employing Cohen's ( 1992 ) categorizations for effect sizes, both the continuous and dichotomous measures revealed small effect sizes (Chen, Cohen, & Chen, 2010 ).”
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“Chen, Cohen, and Chen (2010) stated that small, medium, and large correspond to odds ratios of 0.52, 1.25, and 1.90.”
BackgroundInfluentialLeaving school without qualifications and mental health problems to age 30
Fergusson, D. M., McLeod, G. F. H., & Horwood, L. J. (2014) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-014-0971-4 · Cited by 13
Bringing humor theory into practice: An interdisciplinary approach to online humor training
Baisley, M. C., & Grunberg, N. E. (2019) · New Ideas in Psychology · doi:10.1016/j.newideapsych.2019.04.006 · Cited by 15
Norris, A. L., López, G., & Orchowski, L. M. (2020) · Journal of Interpersonal Violence · doi:10.1177/0886260520951308 · Cited by 12
“02]), as indicated by medium-to-large effect sizes (Chen et al., 2010).”
BackgroundInfluentialla Ruelle, L. P. D., de Zoete, A., de Boer, M. R., van Tulder, M. W., Ostelo, R., & Rubinstein, S. M. (2022) · Chiropractic & Manual Therapies · doi:10.1186/s12998-022-00437-1 · Cited by 12
“5) relations were defined a priori [30, 31].”
Ng, W. Q., & Hartanto, A. (2022) · Social Science & Medicine · doi:10.1016/j.socscimed.2022.115478 · Cited by 12
Predictors, prevalence, and patterns of cyberbullying among school-going children and adolescents
Ranjith, P. J., Vranda, M. N., & Kishore, M. T. (2023) · Indian Journal of Psychiatry · doi:10.4103/indianjpsychiatry.indianjpsychiatry_313_23 · Cited by 18
“[20] According to the findings, fathers with only a basic education were the most reliable predictors of the only cyber-offender (odds ratio (OR): 4.472 [95% confidence interval (CI): 1.195–16.733]; P < 0.02).”
InfluentialLifetime risk of severe kidney disease in lithium-treated patients: a retrospective study
Golic, M., Aiff, H., Attman, P., Ramsauer, B., Schön, S., Steingrímsson, S., & Svedlund, J. (2023) · International Journal of Bipolar Disorders · doi:10.1186/s40345-023-00319-2 · Cited by 12
“Opinions differ, some authors (Davies et al. 1998), consider that the disease rate should fall below 20%, others (Chen et al. 2010)—below 10%, for a reasonable “safe” use of OR.”
BackgroundMethodInfluentialPromoting recycling behaviours through convenience: Focus on the relatives, not the absolute
Soon, D. W. X. (2024) · Cleaner Waste Systems · doi:10.1016/j.clwas.2024.100135 · Cited by 12
Nikolaeva, J. I., Manning, B. L., Kwok, E. Y. L., Choi, S. J., Zhang, Y., Giase, G. M., Wakschlag, L. S., & Norton, E. S. (2024) · Brain and Language · doi:10.1016/j.bandl.2024.105462 · Cited by 12
Allami, Y., Gooding, N. B., Young, M. M., & Hodgins, D. C. (2024) · Journal of Gambling Studies · doi:10.1007/s10899-024-10356-w · Cited by 12
“Effect size interpretations for ORs depend upon the median comparator group risk (MCGR) for the comparator of interest (Chen et al., 2010 ).”
Forrest, L. N., Bennett, B. L., Beccia, A. L., Puhl, R. M., & Watson, R. J. (2025) · International Journal of Eating Disorders · doi:10.1002/eat.24352 · Cited by 12
“Though some odds ratios were statistically significant, all correspond to small effect sizes (Chen, Cohen, and Chen 2010).”
Wright-Hughes, A. M., Farrin, A. J., Fonagy, P., Ougrin, D., Stahl, D. R., Wright, J. M., Irving, D., Mughal, F., Truscott, A., Diggins, E., et al. (2025) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2025.01.017 · Cited by 15
Storkel, H. L., Bontempo, D. E., & Pak, N. S. (2014) · Journal of Speech Language and Hearing Research · doi:10.1044/2014_jslhr-l-13-0150 · Cited by 12
“5 are interpreted as small effects, those near 2–3 are interpreted as moderate effects, and those near 5–6 and higher are considered large effects (Chen et al., 2010).”
Age predicts the absence of caloric-induced vertigo
Jacobson, G. P., Piker, E. G., Grantham, S. L., & English, L. N. (2017) · Journal of Otology · doi:10.1016/j.joto.2017.10.005 · Cited by 12
“Although age was a significant predictor for an absence of motion perception during the caloric exam, the effect size was small (Chen et al., 2010).”
BackgroundJuror Perceptions of Intoxicated Suspects’ Interrogation-Related Behaviors
Mindthoff, A., Evans, J. R., Perez, G., Woestehoff, S. A., Olaguez, A. P., Klemfuss, J. Z., Vallano, J. P., Woody, W. D., Normile, C. J., Scherr, K. C., et al. (2019) · Criminal Justice and Behavior · doi:10.1177/0093854819888962 · Cited by 12
“There are also a few potential limitations of Study 2’s methodology that could have contributed to the small-to-moderate effect sizes we obtained (see Chen et al., 2010, for ORs effect size cutoffs).”
BackgroundKim, Y., Skalicky, S., & Jung, Y. (2020) · Language Learning · doi:10.1111/lang.12393 · Cited by 14
Ayuso, D. M. R., Cuerda, C., Morales, C., Tesoriero, R., Triviño-Juárez, J. M., Segura‐Fragoso, A., & Gallud, J. A. (2021) · Brain Sciences · doi:10.3390/brainsci11020213 · Cited by 12
“For the case of a binary logistic regression, with a dichotomous dependent variable, an interpretation of the OR is proposed based on a transformation to Cohen’s d (d) [31], as follows: OR ≤ 1.”
MethodSchwille‐Kiuntke, J., Rüdlin, S. L., Junne, F., Enck, P., Brenk-Franz, K., Zipfel, S., & Rieger, M. A. (2021) · BMC Family Practice · doi:10.1186/s12875-021-01499-5 · Cited by 14
“5 ⇒ large effect size [32, 33] Subscale/Dimension medication users medication non-users”
BackgroundInfluentialHay, J. L., Kaphingst, K. A., Buller, D. B., Schofield, E., White, K. M., Sussman, A. L., Guest, D. D., Dailey, Y. T., Robers, E., Schwartz, M., et al. (2021) · Cancers · doi:10.3390/cancers13164053 · Cited by 12
“71 were considered small, medium, and large effects [68].”
BackgroundNot just stimuli structure: Sequencing effects in category learning vary by task demands.
Yan, V. X., & Schuetze, B. A. (2021) · Journal of Applied Research in Memory and Cognition · doi:10.1016/j.jarmac.2021.09.004 · Cited by 15
Metadata
- Authors
- Chen, H., Cohen, P., & Chen, S.
- Affiliations
- Winthrop-University Hospital (US)
- New York State Psychiatric Institute (US)
- Health Canada (CA)
- Corresponding author
- Chen, Henian
- Venue
- Communications in Statistics - Simulation and Computation
- Publisher
- Informa UK Limited
- Published
- 2010-03-31
- Volume
- 39
- Issue
- 4
- Pages
- 860-864
- ISSN
- 0361-0918 (ISSN-L)
- 1532-4141
- OpenAlex
- W2029059557
- Cited by
- 1,952
- References
- 20
- Citations by year
- 2026: 170 · 2025: 201 · 2024: 259 · 2023: 234 · 2022: 254 · 2021: 242 · 2020: 196 · 2019: 123 · 2018: 93 · 2017: 65 · 2016: 44 · 2015: 31 · 2014: 18 · 2013: 11 · 2012: 4
- FWCI
- 5.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Communications in Statistics - Simulation and Computation (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- odds ratio, effect size interpretation, Cohen's d, standardized mean difference, disease incidence
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