Odds Ratios for Mediation Analysis for a Dichotomous Outcome
Open accessAbstract
For dichotomous outcomes, the authors discuss when the standard approaches to mediation analysis used in epidemiology and the social sciences are valid, and they provide alternative mediation analysis techniques when the standard approaches will not work. They extend definitions of controlled direct effects and natural direct and indirect effects from the risk difference scale to the odds ratio scale. A simple technique to estimate direct and indirect effect odds ratios by combining logistic and linear regressions is described that applies when the outcome is rare and the mediator continuous. Further discussion is given as to how this mediation analysis technique can be extended to settings in which data come from a case-control study design. For the standard mediation analysis techniques used in the epidemiologic and social science literatures to be valid, an assumption of no interaction between the effects of the exposure and the mediator on the outcome is needed. The approach presented here, however, will apply even when there are interactions between the effect of the exposure and the mediator on the outcome.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
For a rare outcome such as neonatal hyperbilirubinemia, the proportion-mediated can be used to measure how much of the effect of MCoC on each outcome is mediated through preterm birth.
“For a rare outcome such as neonatal hyper bilirubinemia, the proportion-mediated (%) can be used to measure how much of the effect of MCoC on each outcome is mediated through pre term birth (VanderWeele and Vansteelandt, 2010).”
From Midwifery continuity of care, breastfeeding and neonatal hyperbilirubinemia: A retrospective cohort study (2024) · cites this paper as VanderWeele and Vansteelandt, 2010
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Baron, R. M., & Kenny, D. A. (1986) · Journal of Personality and Social Psychology · doi:10.1037//0022-3514.51.6.1173 · Cited by 91,542 · see citing works
Baron, R. M., & Kenny, D. A. (1986) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.51.6.1173 · Cited by 91,532 · see citing works
Causality: Models, Reasoning, and Inference
Pearl, J. (2009) · doi:10.1017/cbo9780511803161 · Cited by 11,653 · see citing works
Introduction to Statistical Mediation Analysis
MacKinnon, D. P. (2012) · doi:10.4324/9780203809556 · Cited by 5,618 · see citing works
Marginal Structural Models and Causal Inference in Epidemiology
Robins, J. M., Hernán, M. Á., & Brumback, B. (2000) · Epidemiology · doi:10.1097/00001648-200009000-00011 · Cited by 5,581 · see citing works
A general approach to causal mediation analysis.
Imai, K., Keele, L., & Tingley, D. (2010) · Psychological Methods · doi:10.1037/a0020761 · Cited by 4,143 · see citing works
The Protective Effects of Estrogen on the Cardiovascular System
Mendelsohn, M. E., & Karas, R. H. (1999) · New England Journal of Medicine · doi:10.1056/nejm199906103402306 · Cited by 3,108 · see citing works
Process Analysis: Estimating Mediation in Treatment Evaluations
Judd, C. M., & Kenny, D. A. (1981) · Evaluation Review · doi:10.1177/0193841x8100500502 · Cited by 2,442 · see citing works
Identifiability and exchangeability for direct and indirect effects
Robins, J. M., & Greenland, S. (1992) · Epidemiology · doi:10.1097/00001648-199203000-00013 · Cited by 1,793 · see citing works
Bush, T. L., Barrett-Connor, E. L., Cowan, L. D., Criqui, M. H., Wallace, R. B., Suchindran, C., Tyroler, H. A., & Rifkind, B. M. (1987) · Circulation · doi:10.1161/01.cir.75.6.1102 · Cited by 1,346 · see citing works
Pearl, J. (2022) · ACM eBooks · doi:10.1145/3501714.3501736 · Cited by 1,039 · see citing works
Confounding and Collapsibility in Causal Inference
Greenland, S., Pearl, J., & Robins, J. M. (1999) · Statistical Science · doi:10.1214/ss/1009211805 · Cited by 933 · cited 1× · see citing works
“Second, the methods described above require a rare outcome; this was necessary in the derivations and also circumvents collapsibility issues with odds ratios (39); some existing work considers or could be adapted for non-rare outcomes (16, 40); future work will consider settings in which the outcome is not rare and co…”
Conceptual issues concerning mediation, interventions and composition
VanderWeele, T. J., & Vansteelandt, S. (2009) · Statistics and Its Interface · doi:10.4310/sii.2009.v2.n4.a7 · Cited by 731 · see citing works
Self-citationStatistical validation of intermediate endpoints for chronic diseases
Freedman, L. S., Graubard, B. I., & Schatzkin, A. G. (1992) · Statistics in Medicine · doi:10.1002/sim.4780110204 · Cited by 651 · see citing works
Marginal Structural Models for the Estimation of Direct and Indirect Effects
VanderWeele, T. J. (2009) · Epidemiology · doi:10.1097/ede.0b013e31818f69ce · Cited by 583 · see citing works
Self-citationFallibility in estimating direct effects
Cole, S. R., & Hernán, M. A. (2002) · International Journal of Epidemiology · doi:10.1093/ije/31.1.163 · Cited by 548 · see citing works
ESTIMATING THE PROPORTION OF TREATMENT EFFECT EXPLAINED BY A SURROGATE MARKER
Lin, D. Y., Fleming, T. R., & Gruttola, V. D. (1997) · Statistics in Medicine · doi:10.1002/(sici)1097-0258(19970715)16:13 · Cited by 520 · see citing works
Formal mode of statistical inference for causal effects
Rubin, D. B. (1990) · Journal of Statistical Planning and Inference · doi:10.1016/0378-3758(90)90077-8 · Cited by 483 · see citing works
A definition of causal effect for epidemiological research
Hernán, M. Á. (2004) · Journal of Epidemiology & Community Health · doi:10.1136/jech.2002.006361 · Cited by 455 · see citing works
Bias Formulas for Sensitivity Analysis for Direct and Indirect Effects
VanderWeele, T. J. (2010) · Epidemiology · doi:10.1097/ede.0b013e3181df191c · Cited by 435 · see citing works
Self-citationConcerning the Consistency Assumption in Causal Inference
VanderWeele, T. J. (2009) · Epidemiology · doi:10.1097/ede.0b013e3181bd5638 · Cited by 368 · see citing works
Self-citationComputation, Causation, and Discovery
(1999) · AAAI Press eBooks · doi:10.7551/mitpress/2006.001.0001 · Cited by 355 · see citing works
Highly Structured Stochastic Systems
Green, P. J. (2003) · CERN Document Server (European Organization for Nuclear Research) · Cited by 332 · see citing works
Kaufman, J. S., MacLehose, R. F., & Kaufman, S. (2004) · Epidemiologic Perspectives & Innovations · doi:10.1186/1742-5573-1-4 · Cited by 253 · see citing works
Identifiability of path-specific effects
Avin, C., Shpitser, I., & Pearl, J. (2005) · eScholarship (California Digital Library) · Cited by 215 · see citing works
Related Causal Frameworks for Surrogate Outcomes
Joffe, M. M., & Greene, T. (2008) · Biometrics · doi:10.1111/j.1541-0420.2008.01106.x · Cited by 200 · see citing works
Estimating Direct Effects in Cohort and Case–Control Studies
Vansteelandt, S. (2009) · Epidemiology · doi:10.1097/ede.0b013e3181b6f4c9 · Cited by 159 · see citing works
Self-citationCausal Mediation Analyses with Rank Preserving Models
Have, T. R. T., Joffe, M. M., Lynch, K. G., Brown, G. K., Maisto, S. A., & Beck, A. T. (2007) · Biometrics · doi:10.1111/j.1541-0420.2007.00766.x · Cited by 157 · see citing works
A method to assess the proportion of treatment effect explained by a surrogate endpoint
Li, Z., Meredith, M. P., & Hoseyni, M. S. (2001) · Statistics in Medicine · doi:10.1002/sim.984 · Cited by 153 · see citing works
VanderWeele, T. J. (2009) · European Journal of Epidemiology · doi:10.1007/s10654-009-9331-1 · Cited by 143 · see citing works
Self-citationShenassa, E. D., Daskalakis, C., Liebhaber, A., Braubach, M., & Brown, M. (2007) · American Journal of Public Health · doi:10.2105/ajph.2006.093773 · Cited by 125 · see citing works
Dunn, G., & Bentall, R. P. (2007) · Statistics in Medicine · doi:10.1002/sim.2891 · Cited by 118 · see citing works
Estimation of Controlled Direct Effects
Goetgeluk, S., Vansteelandt, S., & Goetghebeur, E. (2008) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2008.00673.x · Cited by 104 · see citing works
Self-citationA Measure of the Proportion of Treatment Effect Explained by a Surrogate Marker
Wang, Y., & Taylor, J. M. G. (2002) · Biometrics · doi:10.1111/j.0006-341x.2002.00803.x · Cited by 101 · see citing works
van der Laan, M. J., & Petersen, M. L. (2008) · The International Journal of Biostatistics · doi:10.2202/1557-4679.1064 · Cited by 100 · see citing works
“Proportion explained”: a causal interpretation for standard measures of indirect effect?
Hafeman, D. M. (2009) · American Journal of Epidemiology · doi:10.1093/aje/kwp283 · Cited by 98 · see citing works
Statistical assessment of mediational effects for logistic mediational models
Huang, B., Sivaganesan, S., Succop, P., & Goodman, E. (2004) · Statistics in Medicine · doi:10.1002/sim.1847 · Cited by 89 · see citing works
Chanock, S. J., & Hunter, D. J. (2008) · Nature · doi:10.1038/452537a · Cited by 86 · see citing works
Counterfactual Links to the Proportion of Treatment Effect Explained by a Surrogate Marker
Taylor, J. M. G., Wang, Y., & Thiébaut, R. (2005) · Biometrics · doi:10.1111/j.1541-0420.2005.00380.x · Cited by 78 · see citing works
Joffe, M. M., Small, D. S., & Hsu, C. (2007) · Cited by 71 · see citing works
Estimation Based on Case-Control Designs with Known Prevalence Probability
van der Laan, M. J. (2008) · The International Journal of Biostatistics · doi:10.2202/1557-4679.1114 · Cited by 67 · see citing works
Defining and Estimating Intervention Effects for Groups that will Develop an Auxiliary Outcome
Joffe, M. M., Small, D., & Hsu, C.-Y. (2007) · Statistical Science · doi:10.1214/088342306000000655 · Cited by 66 · see citing works
Vansteelandt, S., Goetgeluk, S., Lutz, S. M., Waldman, I. D., Lyon, H. N., Schadt, E. E., Weiss, S. T., & Lange, C. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20393 · Cited by 52 · see citing works
Self-citationProportion of treatment effect (PTE) explained by a surrogate marker
Chen, C., Wang, H., & Snapinn, S. M. (2003) · Statistics in Medicine · doi:10.1002/sim.1575 · Cited by 38 · see citing works
Wacholder, S., Chatterjee, N., & Caporaso, N. E. (2008) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djn380 · Cited by 22 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Robins JM. Testing and estimation of direct effects by repar- ameterizing directed acyclic graphs with structural nested models. In: Glymour C, Cooper GF, eds. Computation, Cau- sation, and Discovery. Menlo Park, CA: AAAI Press/ Cambridge, MA: The MIT Press; 1999:349-405.
Cited by
Sorted by citations
Statistical mediation analysis with a multicategorical independent variable
Hayes, A. F., & Preacher, K. J. (2014) · British Journal of Mathematical and Statistical Psychology · doi:10.1111/bmsp.12028 · Cited by 3,403 · see citing works
Mediation Analysis: A Practitioner's Guide
VanderWeele, T. J. (2016) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-032315-021402 · Cited by 1,985 · see citing works
Self-citationThe Table 2 Fallacy: Presenting and Interpreting Confounder and Modifier Coefficients
Westreich, D., & Greenland, S. (2013) · American Journal of Epidemiology · doi:10.1093/aje/kws412 · Cited by 1,276 · see citing works
Mendelian randomisation for mediation analysis: current methods and challenges for implementation
Carter, A. R., Sanderson, E., Hammerton, G., Richmond, R. C., Davey Smith, G., Heron, J., Taylor, A. E., Davies, N. M., & Howe, L. D. (2021) · European Journal of Epidemiology · doi:10.1007/s10654-021-00757-1 · Cited by 1,215 · see citing works
Mediation analysis with multiple mediators
VanderWeele, T., & Vansteelandt, S. (2014) · Epidemiologic Methods · doi:10.1515/em-2012-0010 · Cited by 858 · see citing works
Self-citationVanderWeele, T. J., & Robinson, W. R. (2014) · Epidemiology · doi:10.1097/ede.0000000000000105 · Cited by 567 · see citing works
Self-citationMethodological Challenges in Mendelian Randomization
VanderWeele, T. J., Tchetgen Tchetgen, E. J., Cornelis, M., & Kraft, P. (2014) · Epidemiology · doi:10.1097/ede.0000000000000081 · Cited by 555 · see citing works
Self-citationBurgess, S., Daniel, R. M., Butterworth, A. S., Thompson, S. G., & the EPIC-InterAct Consortium (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyu176 · Cited by 543 · see citing works
Agerbo, E., Sullivan, P. F., Vilhjálmsson, B. J., Pedersen, C. B., Mors, O., Børglum, A. D., Hougaard, D. M., Hollegaard, M. V., Meier, S., Mattheisen, M., et al. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.0346 · Cited by 319 · see citing works
Burgess, S., Thompson, D. J., Rees, J. M. B., Day, F. R., Perry, J. R., & Ong, K. K. (2017) · Genetics · doi:10.1534/genetics.117.300191 · Cited by 197 · see citing works
Age at Menarche and Type 2 Diabetes Risk
Elks, C. E., Ong, K. K., Scott, R. A., van der Schouw, Y. T., Brand, J. S., Wark, P. A., Amiano, P., Balkau, B., Barricarte, A., Boeing, H., et al. (2013) · Diabetes Care · doi:10.2337/dc13-0446 · Cited by 186 · see citing works
Detecting moderator effects using subgroup analyses
Wang, R., & Ware, J. H. (2013) · Prevention Science · doi:10.1007/s11121-011-0221-x · Cited by 165 · see citing works
Mair, C., Cunradi, C. B., & Todd, M. (2012) · Annals of Epidemiology · doi:10.1016/j.annepidem.2012.09.008 · Cited by 145 · see citing works
Engel, S. M., Villanger, G. D., Nethery, R. C., Thomsen, C., Sakhi, A. K., Drover, S. S. M., Hoppin, J. A., Zeiner, P., Knudsen, G. P., Reichborn-Kjennerud, T., et al. (2018) · Environmental Health Perspectives · doi:10.1289/ehp2358 · Cited by 143 · see citing works
Flexible Mediation Analysis With Multiple Mediators
Steen, J., Loeys, T., Moerkerke, B., & Vansteelandt, S. (2017) · American Journal of Epidemiology · doi:10.1093/aje/kwx051 · Cited by 123 · see citing works
Self-citationAnanth, C. V., & VanderWeele, T. J. (2011) · American Journal of Epidemiology · doi:10.1093/aje/kwr045 · Cited by 123 · see citing works
Tchetgen Tchetgen, E. J., & VanderWeele, T. J. (2014) · Epidemiology · doi:10.1097/ede.0000000000000054 · Cited by 93 · see citing works
Self-citationJoint analysis of SNP and gene expression data in genetic association studies of complex diseases
Huang, Y.-T., VanderWeele, T. J., & Lin, X. (2014) · The Annals of Applied Statistics · doi:10.1214/13-aoas690 · Cited by 88 · see citing works
Self-citationPeer victimization and suicidal thoughts and behaviors in depressed adolescents
Stewart, J. G., Valeri, L., Esposito, E. C., & Auerbach, R. P. (2018) · Journal of Abnormal Child Psychology · doi:10.1007/s10802-017-0304-7 · Cited by 60 · see citing works
Hazzard, V. M., Bauer, K. W., Mukherjee, B., Miller, A. L., & Sonneville, K. R. (2019) · Child Abuse & Neglect · doi:10.1016/j.chiabu.2019.104171 · Cited by 59 · see citing works
Augustyn, M. B., Thornberry, T. P., & Henry, K. L. (2019) · Development and Psychopathology · doi:10.1017/s0954579418001633 · Cited by 42 · see citing works
Prenatal ambient air pollution exposure and SOD2 promoter methylation in maternal and cord blood
Zhou, G., He, T., Huang, H., Feng, F., Liu, X., Li, Z., Zhang, Y., & Ba, Y. (2019) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2019.06.039 · Cited by 35 · see citing works
Kondracki, A. J., Valente, M. J., Ibrahimou, B., & Bursac, Z. (2022) · Paediatric and Perinatal Epidemiology · doi:10.1111/ppe.12809 · Cited by 34 · see citing works
More powerful genetic association testing via a new statistical framework for integrative genomics
Zhao, S. D., Cai, T. T., & Li, H. (2014) · Biometrics · doi:10.1111/biom.12206 · Cited by 31 · see citing works
Neurodevelopmental outcomes in children in relation to placental abruption
Ananth, C., Friedman, A., Lavery, J., VanderWeele, T., Keim, S., & Williams, M. (2017) · BJOG: An International Journal of Obstetrics & Gynaecology · doi:10.1111/1471-0528.14049 · Cited by 30 · see citing works
Self-citationNabi, R., & Shpitser, I. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11553 · Cited by 20 · see citing works
Shahshahani, M. A., Liu, X., Norman, M., Tilden, E. L., & Ahlberg, M. (2024) · Midwifery · doi:10.1016/j.midw.2024.104079 · Cited by 7 · see citing works
- Authors
- VanderWeele, T. J., & Vansteelandt, S.
- Affiliations
- Harvard University (US)
- Corresponding author
- VanderWeele, T. J.
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-10-29
- Volume
- 172
- Issue
- 12
- Pages
- 1339-1348
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- PMC
- PMC2998205
- OpenAlex
- W2132617827
- Cited by
- 809
- References
- 45
- Citations by year
- 2026: 51 · 2025: 55 · 2024: 69 · 2023: 67 · 2022: 64 · 2021: 63 · 2020: 71 · 2019: 51 · 2018: 58 · 2017: 45 · 2016: 43 · 2015: 40 · 2014: 46 · 2013: 36 · 2012: 36
- FWCI
- 23.47
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- American Journal of Epidemiology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- World Health Organization
- Universiteit Gent (P06/03)
- National Institutes of Health (ES017876)
- National Institute of Environmental Health Sciences (ES017876, R01ES017876, R56ES017876)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R03HD060696, HD060696)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- mediation analysis, binary outcomes, controlled direct effect, natural direct and indirect effects, case-control study
- MeSH terms
- Humans, Reproducibility of Results, Causality, Linear Models, Logistic Models, Odds Ratio, Case-Control Studies, Treatment Outcome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
