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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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“Overall, the prevalence of alcohol use and misuse in this study is similar to that found in other national surveys in the USA (Chen et al., 2013).”
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“Guidelines for interpreting odds ratios followed Chen et al. (2010) calculations.”
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“However, as a general rule of thumb, and following the recommendation of Chen et al. (2010), OR between 1 and 1.68 usually indicate small effects, OR between 1.68 and 3.47 indicate medium effects, and OR greater than 3.47 generally indicate fairly large effects, which are equivalent to Cohen’s d =…”
InfluentialSwirbul, M. S., Shahnooshi, M., Ho, R., & Tamis‐LeMonda, C. S. (2024) · Journal of Cognition and Development · doi:10.1080/15248372.2024.2338725 · Cited by 9
“Odds ratios can be interpreted as effect sizes ranging from 0 to infinity, where 1 represents no association (e.g., a particular social cue is equally likely to occur across types of math talk), with effect sizes being interpretable as weak, moderate, or strong (Chen et al., 2010).”
Lengvenytė, A., Cognasse, F., Hamzeh‐Cognasse, H., Sénèque, M., Strumila, R., Olié, É., & Courtet, P. (2024) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2024.107119 · Cited by 11
“…in this manuscript was exploratory and no statistical method was used to predetermine sample size, but the post-hoc sensitivity analysis indicated that the present analysis achieved a power of 0.85 based on a sample of 139 individuals, and was able to detect small effect sizes (Chen et al., 2010).”
MethodInfluentialAly, N. M., Ihab, M., Ammar, N., Quritum, M., Moussa, H., & Tantawi, M. E. (2024) · BMC Oral Health · doi:10.1186/s12903-024-04454-9 · Cited by 9
“We made sure that the present study was adequately powered to detect at least a small effect size based on an odds ratio = 1.5 [31] or 1.68 [32] of the impact of oral health on daily lives assuming different distributions of the independent variables where a maximum of 179 participants would be…”
BackgroundInfluentialHyde-Smith, C., Carey, H., & Steward, T. (2024) · Journal of Eating Disorders · doi:10.1186/s40337-024-01138-1 · Cited by 11
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“Drawing on data from large population-based samples, our findings may have meaningful implications for both public health and clinical implications [70, 71].”
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“Effect size was classified according to Cohen (1998) for semi-partial correlations and Chen et al. (2010) for Odds Ratios.”
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“However, according to Chen et al. (2010), the effects (odds ratios) were only small.”
BackgroundVance, A. L. A., McGaw, J., Winther, J., White, S., Gone, J. P., & Eades, S. (2023) · Australian & New Zealand Journal of Psychiatry · doi:10.1177/00048674231187315 · Cited by 9
“Chen et al.’s (2010) grading of odds ratio’s into small/medium/large magnitude of clinical effect was used.”
MethodGopez, J. M. W., & Gopez, B. B. (2023) · European Journal of Psychology of Education · doi:10.1007/s10212-023-00728-y · Cited by 11
“The computed minimum total sample size is 107 using input parameters with a Cohen’s effect size convention of 0.15 (Chen et al., 2010; Ferguson, 2009), the alpha at 0.05, and the desired power set at 0.95.”
InfluentialZwar, L., König, H., & Hajek, A. (2023) · International Psychogeriatrics · doi:10.1017/s1041610223000601 · Cited by 10
“We compared our fi ndings with the odds ratio calculated by Chen et al .”
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“For the interpretation of the odds ratio (OR) we followed the criteria suggested by previous research [26] in which an OR with a value between 2 and 3 was considered small, 3–5 medium and above 5 large.”
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“According to Chen, Cohen, and Chen (2010), the strength of the identified associations can be considered low (OR < 1.5), medium (OR 1.5 - 5), or high (OR > 5).”
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“Cohen’s d represents an index of the difference between the two groups that does not depend on the number of samples; regarding the effect size criteria of Cohen’s d, .2, .5, and .8 are defined as small, medium, and large effect sizes, respectively (Chen et al., 2010).”
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“Effect sizes are reported in odds ratios (ORs), with interpretation of magnitude of effects informed by guidelines in the statistical literature [65].”
BackgroundNolan, T. S., Tan, A., & Williams, K. P. (2020) · Journal of Medical Screening · doi:10.1177/0969141320920900 · Cited by 9
“15 for ORs less than one) as cutoffs for small, medium, and large effect sizes.(22) All tests were two-sided with a significance level of 0.”
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“The effect size of 0.2 might be considered as small to medium range, according to Cohen’s criteria (1988) (Cohen, 1988).”
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“4Following Chen, Cohen, and Chen (2010), the statistic is interpreted as follows: OR <1.68 (very small); 1.68 to 3.47 (small); 3.47 to 6.71 (medium); > 6.71 (very large).”
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“Both relationships showed a median effect magnitude, according to the equivalence established with Cohen’s d (Chen et al., 2010).”
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“For logistic regression models, effect sizes are reported as odds ratios (OR: 1.68 = small, 3.47 = medium, 6.71 = large; Chen et al., 2010).”
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“Crucially, following the established thresholds for interpreting the size of odds ratios, this effect size is considered small (i.e., OR < 3.47; Chen et al., 2010).”
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“This OR of 1.56 is a small effect size, and Chen et al. [45] established conventions of small, medium, and large ORs (similar to Cohen’s magnitudes of effect size, d ).”
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“32 Previous studies have shown similar results regardless of the clinical setting and type or characteristics of the dysphagia.”
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“The input parameters with a Cohen’s effect size convention of α = 0.15 [53, 54], the alpha at α = 0.05, and the desired power set at CI = 0.95 results in a computed minimum total sample size of 107.”
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“…reporting results were: quality assessment, sample size, de-sign, degree of error in measurement of conflict and containment and staffing variables, statistical significance, magnitude of effect size (adapted from Cohen 1988; Chen et al. 2010), precision (confidence intervals) and generalisability.”
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“We interpreted odds ratios up to 3.47 as small and those larger than 6.71 as large (Chen et al. 2010).”
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“Using this figure as a baseline, an odds ratio of OR = 1.37 or 0.73 represents a small effect (Chen et al., 2010), amounting to an increase to p = 0.51 or 51%.”
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“In other instances, the effect was small (33).”
Reyes, C. T., Cao, W., Astorini, A. G., Drohan, M. M., Schulz, C. T., Shuster, C. L., Robbins, M. L., Yang, M., & Stamates, A. L. (2023) · Health Psychology and Behavioral Medicine · doi:10.1080/21642850.2023.2248236 · Cited by 8
“Rather than focusing on generalizability to the population at large, this study seeks to describe attitudes within a specific subgroup in the population (Chen et al., 2010).”
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Spence, K., Merkouris, S., Jackson, A. C., Wade, A., & Dowling, N. A. (2024) · Addictive Behaviors · doi:10.1016/j.addbeh.2024.107998 · Cited by 8
Swimming for low back pain: A scoping review
Wareham, D. M., FULLER, J. T., Douglas, T. J., Han, C. S., & Hancock, M. J. (2024) · Musculoskeletal Science and Practice · doi:10.1016/j.msksp.2024.102926 · Cited by 8
Pathways from school to work: A sequence analysis of non‐engaged youth
Ngai, S. S., Cheung, C., Ng, Y., Lee, B. J., Dupéré, V., Wang, M., Chen, C., Li, Y., Zhou, Q., Wong, L., et al. (2024) · Journal of Adolescence · doi:10.1002/jad.12372 · Cited by 8
Improving and Analyzing Open-Ended Survey Responses
Hahn, S., Kroehne, U., & Merk, S. (2024) · Zeitschrift für Psychologie · doi:10.1027/2151-2604/a000566 · Cited by 8
Gavilán‐Carrera, B., Aguilera-Fernández, V., Amaro‐Gahete, F. J., Rosales‐Castillo, A., Soriano‐Maldonado, A., & Vargas‐Hitos, J. A. (2024) · The Journal of Nutritional Biochemistry · doi:10.1016/j.jnutbio.2024.109759 · Cited by 8
Bye, J. K., Chan, J. Y., Closser, A. H., Lee, J., Shaw, S. T., & Ottmar, E. (2024) · Journal of Numerical Cognition · doi:10.5964/jnc.14103 · Cited by 8
“The minimum detectable effect size at 80% power is an odds ratio of 1.39 (or 0.72), which is below the “weak association” benchmark of Chen et al. (2010) and approximately one-fifth of the effect size observed in the pilot data (Bye et al., 2022).”
InfluentialNweke, M., Oyirinnaya, P., Nwoha, P. U., Mitha, S. B., Mshunqane, N., Govender, N., Ukwuoma, M., & Ibeneme, S. C. (2025) · BMC Neurology · doi:10.1186/s12883-025-04229-x · Cited by 9
Lesion severity at processing as a predictor of Salmonella contamination of swine carcasses
Hurd, H. S., Yaeger, M. J., Brudvig, J. M., Taylor, D. D., & Wang, B. (2011) · American Journal of Veterinary Research · doi:10.2460/ajvr.73.1.91 · Cited by 8
Correlates of Worry About Health Care Costs Among Older Adults
Choi, N. G., & DiNitto, D. M. (2016) · Journal of Applied Gerontology · doi:10.1177/0733464816650803 · Cited by 8
Lucabeche, V. X., & Haney, J. L. (2018) · Journal of Substance Abuse Treatment · doi:10.1016/j.jsat.2018.04.005 · Cited by 9
Cartwright, J. K., Desmarais, S. L., Johnson, K. L., & Dorn, R. A. V. (2018) · Psychological Services · doi:10.1037/ser0000183 · Cited by 8
Choi, N. G., Marti, C. N., DiNitto, D. M., & Choi, B. Y. (2019) · Archives of Suicide Research · doi:10.1080/13811118.2019.1592042 · Cited by 8
Morales-Castillo, M., Aguirre-Dávila, E., & Durán-Urrea, L. (2019) · Saúde e Sociedade · doi:10.1590/s0104-12902019181111 · Cited by 8
Kim, Y., Lee, S., Kim, J., Park, E., & Jang, S. (2019) · BMC Oral Health · doi:10.1186/s12903-019-0953-8 · Cited by 8
“In order to interpret effect sizes of odds ratios, the odds ratios were converted into Cohen’s d, or the standardized mean difference between two group means [22].”
MethodVerb Intergroup Bias: Verbs Are Used More Often in Reference to In-Groups than Out-Groups
Formanowicz, M. (2020) · Social Psychological and Personality Science · doi:10.1177/1948550619893957 · Cited by 8
“In all studies, the size of the OR was interpreted according to the recommendations of Chen, Cohen, and Chen (2010).”
MethodDai, W., Palmer, R., Sunderrajan, A., Durantini, M. R., Sánchez, F., Glasman, L. R., Chen, F. X., & Albarracín, D. (2020) · Psychology of Addictive Behaviors · doi:10.1037/adb0000586 · Cited by 8
“As shown in Table 2b, changing the correlation between the pre and post measures 2According to Cohen’s tradition (Chen et al., 2010), d = 0.2 is considered a small effect, d = 0.5 is considered a moderate effect, d = 0.8 is considered a large effect.”
MethodInfluentialRaudales, A. M., Darosh, A. G., Contractor, A. A., Schatten, H. T., Dixon–Gordon, K. L., & Weiss, N. H. (2021) · The Journal of Nervous and Mental Disease · doi:10.1097/nmd.0000000000001316 · Cited by 8
“It is also important to note that effect sizes were in the small range (determined using odds ratios; Chen et al., 2010), urging caution when interpreting results.”
BackgroundBunn, P. D. S., Lopes, T. J. A., Terra, B., da Costa, H. F., Souza, M. P., Braga, R. M., Inoue, A., Ribeiro, F. M., Alves, D., & da Silva, E. B. (2021) · Physical Therapy in Sport · doi:10.1016/j.ptsp.2021.08.003 · Cited by 8
Sindermann, C., & Montag, C. (2021) · Current Psychology · doi:10.1007/s12144-021-02100-z · Cited by 10
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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