Mediation analysis with multiple mediators
Open accessAbstract
Recent advances in the causal inference literature on mediation have extended traditional approaches to direct and indirect effects to settings that allow for interactions and non-linearities. In this paper, these approaches from causal inference are further extended to settings in which multiple mediators may be of interest. Two analytic approaches, one based on regression and one based on weighting are proposed to estimate the effect mediated through multiple mediators and the effects through other pathways. The approaches proposed here accommodate exposure-mediator interactions and, to a certain extent, mediator-mediator interactions as well. The methods handle binary or continuous mediators and binary, continuous or count outcomes. When the mediators affect one another, the strategy of trying to assess direct and indirect effects one mediator at a time will in general fail; the approach given in this paper can still be used. A characterization is moreover given as to when the sum of the mediated effects for multiple mediators considered separately will be equal to the mediated effect of all of the mediators considered jointly. The approach proposed in this paper is robust to unmeasured common causes of two or more mediators.
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?
The causal mediation analysis controlled for covariates.
“We conducted causal mediation analysis (CMA) with cortisol suppression (CS) by dexamethasone (DEX) as an exposure variable, HOMA-IR, hs-CRP, hypoxanthine, and GGT as the joint mediators, and metabolites as dependent variables while controlling for covariates (80).”
The sum mediated proportion exceeding 100% could be due to mediators affecting one another, interaction between mediators affecting the outcome, or other mediators with a negative proportion being unaccounted for in the model.
“This observation is possible and could be due to 3 factors: (1) mediators affecting one another, (2) interaction between mediators affecting the outcome, or (3) other mediators with a”
From Mindful attention is inversely associated with pain via mediation by psychological distress in orthopedic patients. (2024) · cites this paper as [52]
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
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
Valeri, L., & VanderWeele, T. J. (2013) · Psychological Methods · doi:10.1037/a0031034 · Cited by 2,132 · see citing works
Self-citationIdentifiability 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
Kotelchuck, M. (1994) · American Journal of Public Health · doi:10.2105/ajph.84.9.1414 · Cited by 1,167 · see citing works
Pearl, J. (2022) · ACM eBooks · doi:10.1145/3501714.3501736 · Cited by 1,039 · see citing works
Odds Ratios for Mediation Analysis for a Dichotomous Outcome
VanderWeele, T. J., & Vansteelandt, S. (2010) · American Journal of Epidemiology · doi:10.1093/aje/kwq332 · Cited by 809 · see citing works
Self-citationLarge Sample Confidence Regions Based on Subsamples under Minimal Assumptions
Politis, D. N., & Romano, J. P. (1994) · The Annals of Statistics · doi:10.1214/aos/1176325770 · Cited by 748 · see citing works
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-citationBias Formulas for Sensitivity Analysis for Direct and Indirect Effects
VanderWeele, T. J. (2010) · Epidemiology · doi:10.1097/ede.0b013e3181df191c · Cited by 435 · cited 1× · see citing works
“Sensitivity analysis for direct and indirect effects are now available for a single mediator (VanderWeele, 2010; Imai et al., 2010) and these approaches could perhaps be applied and extended to settings with multiple mediators.”
BackgroundSelf-citationEffect Decomposition in the Presence of an Exposure-Induced Mediator-Outcome Confounder
VanderWeele, T. J., Vansteelandt, S., & Robins, J. M. (2014) · Epidemiology · doi:10.1097/ede.0000000000000034 · Cited by 395 · see citing works
Self-citationMicali, N., Hagberg, K. W., Petersen, I., & Treasure, J. L. (2013) · BMJ Open · doi:10.1136/bmjopen-2013-002646 · Cited by 384 · see citing works
Imai, K., & Yamamoto, T. (2013) · Political Analysis · doi:10.1093/pan/mps040 · Cited by 381 · see citing works
Tchetgen, E. J. T., & Shpitser, I. (2012) · The Annals of Statistics · doi:10.1214/12-aos990 · Cited by 281 · see citing works
Semantics of causal DAG models and the identification of direct and indirect effects
Robins, J. M. (2003) · doi:10.1093/oso/9780198510550.003.0007 · Cited by 243 · 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
Imputation Strategies for the Estimation of Natural Direct and Indirect Effects
Vansteelandt, S., Bekaert, M., & Lange, T. (2012) · Epidemiologic Methods · doi:10.1515/2161-962x.1014 · Cited by 177 · see citing works
Self-citationGeneralized Causal Mediation Analysis
Albert, J. M., & Nelson, S. S. (2011) · Biometrics · doi:10.1111/j.1541-0420.2010.01547.x · Cited by 156 · 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
Targeted Maximum Likelihood Estimation of Natural Direct Effects
Zheng, W., & van der Laan, M. J. (2012) · The International Journal of Biostatistics · doi:10.2202/1557-4679.1361 · Cited by 91 · see citing works
VanderWeele, T. J., Lantos, J. D., Siddique, J., & Lauderdale, D. S. (2008) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2008.08.001 · Cited by 88 · see citing works
Self-citationDistribution-Free Mediation Analysis for Nonlinear Models with Confounding
Albert, J. M. (2012) · Epidemiology · doi:10.1097/ede.0b013e31826c2bb9 · Cited by 31 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Robins JM Richardson TS Shrout P Alternative graphical causal models and the identification of direct effects Causality and Psychopathology: Finding the Determinants of Disorders and Their Cures 2011 Oxford University Press
Cited by
Sorted by citations
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-citationOwen, M. J., Sawa, A., & Mortensen, P. B. (2016) · The Lancet · doi:10.1016/s0140-6736(15)01121-6 · Cited by 1,870 · 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
A Unification of Mediation and Interaction
VanderWeele, T. J. (2014) · Epidemiology · doi:10.1097/ede.0000000000000121 · Cited by 654 · see citing works
Self-citationA Guideline for Reporting Mediation Analyses of Randomized Trials and Observational Studies
Lee, H., Cashin, A. G., Lamb, S. E., Hopewell, S., Vansteelandt, S., VanderWeele, T. J., MacKinnon, D. P., Mansell, G., Collins, P. G. S., Golub, R. M., et al. (2021) · JAMA · doi:10.1001/jama.2021.14075 · Cited by 559 · see citing works
Self-citationPower, M. C., Adar, S. D., Yanosky, J. D., & Weuve, J. (2016) · NeuroToxicology · doi:10.1016/j.neuro.2016.06.004 · Cited by 422 · see citing works
CMAverse: A Suite of Functions for Reproducible Causal Mediation Analyses
Shi, B., Choirat, C., Coull, B. A., VanderWeele, T. J., & Valeri, L. (2021) · Epidemiology · doi:10.1097/ede.0000000000001378 · Cited by 413 · see citing works
Self-citationCausal Mediation Analysis with Multiple Mediators
Daniel, R., Stavola, B. L. D., Cousens, S. N., & Vansteelandt, S. (2014) · Biometrics · doi:10.1111/biom.12248 · Cited by 319 · see citing works
Self-citationOutcome-Wide Longitudinal Designs for Causal Inference: A New Template for Empirical Studies
VanderWeele, T. J., Mathur, M. B., & Chen, Y. (2020) · Statistical Science · doi:10.1214/19-sts728 · Cited by 311 · see citing works
Self-citationCausal inference for time series
Runge, J., Gerhardus, A., Varando, G., Eyring, V., & Camps‐Valls, G. (2023) · Nature Reviews Earth & Environment · doi:10.1038/s43017-023-00431-y · Cited by 296 · see citing works
Interventional Effects for Mediation Analysis with Multiple Mediators
Vansteelandt, S., & Daniel, R. (2016) · Epidemiology · doi:10.1097/ede.0000000000000596 · Cited by 286 · see citing works
Self-citationmedflex : An R Package for Flexible Mediation Analysis using Natural Effect Models
Steen, J., Loeys, T., Moerkerke, B., & Vansteelandt, S. (2017) · Journal of Statistical Software · doi:10.18637/jss.v076.i11 · Cited by 279 · see citing works
Self-citationVilar‐Gomez, E., Nephew, L. D., Vuppalanchi, R., Gawrieh, S., Mladenovic, A., Pike, F., Samala, N., & Chalasani, N. (2022) · Hepatology · doi:10.1002/hep.32207 · Cited by 277 · see citing works
Nguyen, Q. C., Osypuk, T. L., Schmidt, N. M., Glymour, M. M., & Tchetgen, E. J. T. (2015) · American Journal of Epidemiology · doi:10.1093/aje/kwu278 · Cited by 214 · see citing works
Imbens, G. W. (2020) · Journal of Economic Literature · doi:10.1257/jel.20191597 · Cited by 208 · see citing works
Siddall, B., Ram, A., Jones, M. D., Booth, J., Perriman, D., & Summers, S. J. (2022) · Pain · doi:10.1097/j.pain.0000000000002308 · Cited by 174 · see citing works
Lee, H., Herbert, R., & McAuley, J. H. (2019) · JAMA · doi:10.1001/jama.2018.21973 · Cited by 173 · see citing works
Rossi, A., Panzeri, A., Pietrabissa, G., Manzoni, G. M., Castelnuovo, G., & Mannarini, S. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.02177 · Cited by 166 · see citing works
Kaniuka, A., Pugh, K. C., Jordan, M., Brooks, B., Dodd, J., Mann, A. K., Williams, S. L., & Hirsch, J. K. (2019) · Journal of Gay & Lesbian Mental Health · doi:10.1080/19359705.2018.1560385 · Cited by 159 · see citing works
McLarnon, M. J. W., & O’Neill, T. (2018) · Organizational Research Methods · doi:10.1177/1094428118770731 · Cited by 153 · see citing works
Rural–urban residence and cancer survival in high‐income countries: A systematic review
Afshar, N., English, D. R., & Milne, R. L. (2019) · Cancer · doi:10.1002/cncr.32073 · Cited by 152 · see citing works
Causal Mediation Analysis of Survival Outcome with Multiple Mediators
Huang, Y., & Yang, H. (2017) · Epidemiology · doi:10.1097/ede.0000000000000651 · Cited by 146 · see citing works
Mediators of the Effects of Canagliflozin on Heart Failure in Patients With Type 2 Diabetes
Li, J., Woodward, M., Perkovic, V., Figtree, G. A., Heerspink, H. J. L., Mahaffey, K. W., de Zeeuw, D., Vercruysse, F., Shaw, W., Matthews, D. R., et al. (2020) · JACC: Heart Failure · doi:10.1016/j.jchf.2019.08.004 · Cited by 144 · see citing works
Das, S. S., & Tiwari, A. K. (2020) · Tourism Recreation Research · doi:10.1080/02508281.2020.1830341 · Cited by 148 · see citing works
Huang, Y., & Pan, W. (2015) · Biometrics · doi:10.1111/biom.12421 · 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-citationFactors Explaining Socio-Economic Inequalities in Cancer Survival: A Systematic Review
Afshar, N., English, D. R., & Milne, R. L. (2021) · Cancer Control · doi:10.1177/10732748211011956 · Cited by 125 · see citing works
High-dimensional multivariate mediation with application to neuroimaging data
Chén, O. Y., Crainiceanu, C. M., Ogburn, E. L., Caffo, B. S., Wager, T. D., & Lindquist, M. A. (2017) · Biostatistics · doi:10.1093/biostatistics/kxx027 · Cited by 121 · see citing works
Eckardt, L., Sehner, S., Suling, A. I., Borof, K., BREITHARDT, G. E., Crijns, H. J. G. M., Goette, A., Wegscheider, K., Zapf, A., Camm, A. J., et al. (2022) · European Heart Journal · doi:10.1093/eurheartj/ehac471 · Cited by 121 · see citing works
Compositional mediation analysis for microbiome studies
Sohn, M. B., & Li, H. (2019) · The Annals of Applied Statistics · doi:10.1214/18-aoas1210 · Cited by 113 · see citing works
Ruiz-Hernandez, A., Navas‐Acién, A., Pastor‐Barriuso, R., Crainiceanu, C. M., Redón, J., Güallar, E., & Téllez-Plaza, M. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx176 · Cited by 108 · see citing works
Hollander, M. A. G., Chang, C. H., Douaihy, A. B., Hulsey, E. G., & Donohue, J. M. (2021) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2021.108927 · Cited by 107 · see citing works
Coutts, J. J., & Hayes, A. F. (2022) · Behavior Research Methods · doi:10.3758/s13428-022-01988-0 · Cited by 107 · see citing works
Fazzini, F., Lamina, C., Raftopoulou, A., Koller, A., Fuchsberger, C., Pattaro, C., Fabiola Del Greco, M., Döttelmayer, P., Fendt, L., Fritz, J., et al. (2021) · Journal of Internal Medicine · doi:10.1111/joim.13242 · Cited by 104 · see citing works
Watling, C. Z., Schmidt, J. A., Dunneram, Y., Tong, T. Y. N., Kelly, R. K., Knüppel, A., Travis, R. C., Key, T. J., & Perez‐Cornago, A. (2022) · BMC Medicine · doi:10.1186/s12916-022-02256-w · Cited by 108 · see citing works
Causal mediation analysis for longitudinal data with exogenous exposure
Bind, M., VanderWeele, T. J., Coull, B. A., & Schwartz, J. D. (2015) · Biostatistics · doi:10.1093/biostatistics/kxv029 · Cited by 103 · see citing works
Self-citation“Truly free consent”? Clarifying the nature of police legitimacy using causal mediation analysis
Pósch, K., Jackson, J., Bradford, B., & MacQueen, S. (2020) · Journal of Experimental Criminology · doi:10.1007/s11292-020-09426-x · Cited by 106 · see citing works
Imbens, G. W. (2019) · National Bureau of Economic Research · doi:10.3386/w26104 · Cited by 101 · see citing works
Zeng, P., Shao, Z., & Zhou, X. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.05.042 · Cited by 97 · see citing works
Goto, M., Schweizer, M. L., Vaughan‐Sarrazin, M., Perencevich, E. N., Livorsi, D. J., Diekema, D. J., Richardson, K. K., Beck, B. F., ALEXANDER, B. K., & Ohl, M. (2017) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2017.3958 · Cited by 95 · see citing works
Yu, Q., Wu, X., Ли, Б., & Scribner, R. A. (2018) · Statistics in Medicine · doi:10.1002/sim.7977 · Cited by 95 · see citing works
Moore, K. A., Fowkes, F. J. I., Wiladphaingern, J., Wai, N. S., Paw, M. K., Pimanpanarak, M., Carrara, V. I., Raksuansak, J., Simpson, J. A., White, N. J., et al. (2017) · BMC Medicine · doi:10.1186/s12916-017-0863-z · Cited by 83 · see citing works
Wang, C., Hu, J., Blaser, M. J., & Li, H. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz565 · Cited by 88 · see citing works
Davidovic, D., & Harring, N. (2020) · Energy Research & Social Science · doi:10.1016/j.erss.2020.101785 · Cited by 88 · see citing works
Mosenzon, O., Capehorn, M. S., De Remigis, A., Rasmussen, S., Weimers, P., & Rosenstock, J. (2022) · Cardiovascular Diabetology · doi:10.1186/s12933-022-01585-7 · Cited by 91 · see citing works
Vo, T., Superchi, C., Boutron, I., & Vansteelandt, S. (2019) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2019.10.001 · Cited by 85 · see citing works
Self-citationFactors associated with sex differences in the risk of kidney stones
Ferraro, P. M., Taylor, E. N., & Curhan, G. C. (2022) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfac037 · Cited by 84 · see citing works
Murillo, C., Vo, T., Vansteelandt, S., Harrison, L. E., Cagnie, B. J., Coppieters, I., Chys, M., Timmers, I., & Meeus, M. (2022) · Clinical Psychology Review · doi:10.1016/j.cpr.2022.102160 · Cited by 85 · see citing works
Self-citationChu, S. H., Huang, M., Kelly, R., Benedetti, E., Siddiqui, J. K., Zeleznik, O., Pereira, A., Herrington, D., Wheelock, C., Krumsiek, J., et al. (2019) · Metabolites · doi:10.3390/metabo9060117 · Cited by 73 · see citing works
Age-Related Hearing Loss, Late-Life Depression, and Risk for Incident Dementia in Older Adults
Brewster, K., Hu, M., Zilcha‐Mano, S., Stein, A., Brown, P. J., Wall, M. M., Roose, S. P., Golub, J. S., & Rutherford, B. R. (2020) · The Journals of Gerontology Series A · doi:10.1093/gerona/glaa242 · Cited by 76 · see citing works
Runhaar, J., Beavers, D. P., Miller, G. D., Nicklas, B. J., Loeser, R. F., Bierma-Zeinstra, S., & Messier, S. P. (2019) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2019.04.009 · Cited by 75 · see citing works
Bayesian shrinkage estimation of high dimensional causal mediation effects in omics studies
Song, Y., Zhou, X., Zhang, M., Zhao, W., Liu, Y., Kardia, S. L. R., Roux, A. V. D., Needham, B. L., Smith, J. A., & Mukherjee, B. (2019) · Biometrics · doi:10.1111/biom.13189 · Cited by 74 · see citing works
A Tutorial in Bayesian Potential Outcomes Mediation Analysis
Miočević, M., González, O., Valente, M. J., & MacKinnon, D. P. (2017) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2017.1342541 · Cited by 70 · see citing works
Sparse principal component based high-dimensional mediation analysis
Zhao, Y., Lindquist, M. A., & Caffo, B. S. (2019) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2019.106835 · Cited by 70 · see citing works
A pathway level analysis of PFAS exposure and risk of gestational diabetes mellitus
Birru, R. L., Liang, H., Farooq, F., Bedi, M., Feghali, M. N., Haggerty, C. L., Méndez, D. D., Catov, J. M., Ng, C. A., & Adibi, J. J. (2021) · Environmental Health · doi:10.1186/s12940-021-00740-z · Cited by 70 · see citing works
Vansteelandt, S., Linder, M., Vandenberghe, S., Steen, J., & Madsen, J. C. (2019) · Statistics in Medicine · doi:10.1002/sim.8336 · Cited by 70 · see citing works
Self-citationA principled approach to mediation analysis in perinatal epidemiology
Ananth, C. V., & Brandt, J. S. (2022) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2021.10.028 · Cited by 69 · see citing works
Fritz, J., Brozek, W., Concin, H., Nagel, G., Kerschbaum, J., Lhotta, K., Ulmer, H., & Zitt, E. (2022) · Journal of the American Society of Nephrology · doi:10.1681/asn.2021091263 · Cited by 69 · see citing works
Exploratory Mediation Analysis via Regularization
Serang, S., Jacobucci, R., Brimhall, K. C., & Grimm, K. J. (2017) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2017.1311775 · Cited by 69 · see citing works
Xu, R., Hong, X., Zhang, B., Huang, W., Hou, W., Wang, G., Wang, X., Igusa, T., Liang, L., & Ji, H. (2021) · Clinical Epigenetics · doi:10.1186/s13148-021-01032-6 · Cited by 68 · see citing works
Yu, H., & Zhu, Q. (2022) · Environmental Science and Pollution Research · doi:10.1007/s11356-022-22552-5 · Cited by 67 · see citing works
Testing for the indirect effect under the null for genome‐wide mediation analyses
Barfield, R., Shen, J., Just, A. C., Vokonas, P., Schwartz, J. D., Baccarelli, A., VanderWeele, T. J., & Lin, X. (2017) · Genetic Epidemiology · doi:10.1002/gepi.22084 · Cited by 67 · see citing works
Self-citationInoue, K., Yan, Q. J., Arah, O. A., Paul, K. C., Walker, D. I., Jones, D. P., & Ritz, B. R. (2020) · Current Environmental Health Reports · doi:10.1007/s40572-020-00284-3 · Cited by 66 · see citing works
Nguyen, T. Q., Webb-Vargas, Y., Koning, I. M., & Stuart, E. A. (2015) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2015.1062730 · Cited by 64 · see citing works
Afshar, N., English, D. R., Blakely, T. A., Thursfield, V. J., Farrugia, H., Giles, G. G., & Milne, R. L. (2020) · PLoS ONE · doi:10.1371/journal.pone.0228551 · Cited by 63 · see citing works
Leapman, M., Dinan, M. A., Pasha, S., Long, J. B., Washington, S. L., Ma, X., & Gross, C. P. (2022) · JAMA Oncology · doi:10.1001/jamaoncol.2021.8116 · Cited by 61 · see citing works
Fight or flight: Integral emotions and violent intentions
Barnum, T. C., & Solomon, S. J. (2019) · Criminology · doi:10.1111/1745-9125.12222 · Cited by 61 · see citing works
UN Peacekeeping and Households' Well‐Being in Civil Wars
Bove, V., Salvatore, J. D., & Elia, L. (2021) · American Journal of Political Science · doi:10.1111/ajps.12644 · Cited by 60 · see citing works
Vilhjalmsdottir, A., Garðarsdóttir, R. B., Bernburg, J. G., & Sigfúsdóttir, I. D. (2016) · Journal of Adolescence · doi:10.1016/j.adolescence.2016.06.004 · Cited by 60 · see citing works
Burrowes, S. A. B., Goloubeva, O. G., Stafford, K. A., McArdle, P. F., Goyal, M., Peterlin, B. L., Haythornthwaite, J. A., & Seminowicz, D. A. (2021) · Pain · doi:10.1097/j.pain.0000000000002372 · Cited by 59 · see citing works
Martinez, N. T., Xerxa, Y., Law, J., Serdarević, F., Jansen, P. W., & Tiemeier, H. W. (2022) · European Journal of Public Health · doi:10.1093/eurpub/ckac044 · Cited by 57 · see citing works
Understanding how health interventions or exposures produce their effects using mediation analysis
Cashin, A. G., McAuley, J. H., VanderWeele, T. J., & Lee, H. (2023) · BMJ · doi:10.1136/bmj-2022-071757 · Cited by 56 · see citing works
Self-citationCausal mediation analysis with multiple causally non-ordered mediators
Taguri, M., Featherstone, J. D. B., & Cheng, J. (2015) · Statistical Methods in Medical Research · doi:10.1177/0962280215615899 · Cited by 56 · see citing works
Historical Redlining and Contemporary Racial Disparities in Neighborhood Life Expectancy
Graetz, N., & Esposito, M. H. (2022) · Social Forces · doi:10.1093/sf/soac114 · Cited by 54 · see citing works
Keele, L. J. (2015) · American Journal of Evaluation · doi:10.1177/1098214015594689 · Cited by 55 · see citing works
Decomposition of the Total Effect in the Presence of Multiple Mediators and Interactions.
Bellavia, A., & Valeri, L. (2018) · American Journal of Epidemiology · doi:10.1093/aje/kwx355 · Cited by 59 · see citing works
Concentrated poverty, ambient air pollution, and child cognitive development
Wodtke, G. T., Ard, K. J., Bullock, C., White, K., & Priem, B. (2022) · Science Advances · doi:10.1126/sciadv.add0285 · Cited by 54 · see citing works
Moreno-Peral, P., Bellón, J. Á., Huibers, M. J. H., Mestre, J. M., García-López, L. J., Taubner, S., Rodríguez-Morejón, A., Bolinski, F., Sales, C. M. D., & Conejo-Cerón, S. (2020) · Clinical Psychology Review · doi:10.1016/j.cpr.2020.101813 · Cited by 51 · see citing works
Approaches for incorporating environmental mixtures as mediators in mediation analysis
Bellavia, A., James-Todd, T. M., & Williams, P. L. (2018) · Environment International · doi:10.1016/j.envint.2018.12.024 · Cited by 53 · see citing works
Investigating the role of group-based morality in extreme behavioral expressions of prejudice
Hoover, J., Atari, M., Davani, A. M., Kennedy, B., Portillo-Wightman, G., Yeh, L., & Dehghani, M. (2021) · Nature Communications · doi:10.1038/s41467-021-24786-2 · Cited by 51 · see citing works
Rief, R. M., & Clinkinbeard, S. S. (2020) · Police Quarterly · doi:10.1177/1098611120917942 · Cited by 52 · see citing works
Challenges Raised by Mediation Analysis in a High-Dimension Setting
Blum, M. G. B., Valeri, L., François, O., Cadiou, S., Siroux, V., Lepeule, J., & Slama, R. (2020) · Environmental Health Perspectives · doi:10.1289/ehp6240 · Cited by 52 · see citing works
Beaudrap, P. D., Mouté, C., Pasquier, E., Mac-Seing, M., Mukangwije, P. U., & Beninguissé, G. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16030417 · Cited by 51 · see citing works
Causal mediation analysis in presence of multiple mediators uncausally related
Jérolon, A., Baglietto, L., Birmelé, É., Alarcon, F., & Perduca, V. (2020) · The International Journal of Biostatistics · doi:10.1515/ijb-2019-0088 · Cited by 50 · see citing works
Sheikh, M. A., Abelsen, B., & Olsen, J. A. (2017) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2016-208671 · Cited by 50 · see citing works
High Dimensional Mediation Analysis With Latent Variables
Derkach, A., Pfeiffer, R. M., Chen, T., & Sampson, J. N. (2019) · Biometrics · doi:10.1111/biom.13053 · Cited by 49 · see citing works
Rahman, M. L., Valeri, L., Kile, M., Mazumdar, M., Mostofa, G., Qamruzzaman, Q., Rahman, M., Baccarelli, A., Liang, L., Hauser, R., et al. (2017) · Environment International · doi:10.1016/j.envint.2017.07.026 · Cited by 39 · see citing works
Reducing socio-economic inequalities in all-cause mortality: a counterfactual mediation approach
Laine, J. E., Baltar, V. T., Stringhini, S., Gandini, M., Chadeau‐Hyam, M., Mika Kivimaki, B., Severi, G., Perduca, V., Hodge, A. M., Dugué, P., et al. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyz248 · Cited by 48 · see citing works
Rousseau, C., Hassan, G., Miconi, D., Lecompte, V., Mekki‐Berrada, A., El-Hage, H., & Oulhote, Y. (2019) · Archives of Public Health · doi:10.1186/s13690-019-0372-y · Cited by 47 · see citing works
Murphy, K. A., Jackson, J. W., Purnell, T. S., Shaffer, A. A., Haugen, C. E., Chu, N. M., Crews, D. C., Norman, S. P., Segev, D. L., & McAdams‐DeMarco, M. (2020) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.12541019 · Cited by 47 · see citing works
Estimation and inference for the indirect effect in high-dimensional linear mediation models
Zhou, R., Wang, L., & Zhao, S. D. (2020) · Biometrika · doi:10.1093/biomet/asaa016 · Cited by 46 · see citing works
Aitken, Z., Simpson, J. A., Gurrin, L. C., Bentley, R., & Kavanagh, A. M. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx277 · Cited by 45 · see citing works
Exploratory Mediation Analysis with Many Potential Mediators
van Kesteren, E., & Oberski, D. L. (2019) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2019.1588124 · Cited by 45 · see citing works
Guo, X., Li, R., Liu, J., & Zeng, M. (2022) · Journal of the American Statistical Association · doi:10.1080/01621459.2022.2053136 · Cited by 44 · see citing works
Chi, W. E., Huang, S., Jeon, M., Park, E. S., Melguizo, T., & Kezar, A. J. (2022) · Frontiers in Education · doi:10.3389/feduc.2022.886722 · Cited by 44 · see citing works
The health and economic burden of musculoskeletal disorders in Belgium from 2013 to 2018
Gorasso, V., der Heyden, J. V., Pauw, R. D., Pelgrims, I., Clercq, E. M. D., Ridder, K. D., Vandevijvere, S., Vansteelandt, S., Vaes, B., Smedt, D. D., et al. (2023) · Population Health Metrics · doi:10.1186/s12963-023-00303-z · Cited by 44 · see citing works
Self-citationFamily functioning as perceived by parents and young offspring at high and low risk for depression
Daches, S., Vine, V., Layendecker, K. M., George, C. J., & Kovács, M. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.09.031 · Cited by 44 · see citing works
Rudolph, K. E., Goin, D. E., Paksarian, D., Crowder, R. R., Merikangas, K. R., & Stuart, E. A. (2018) · American Journal of Epidemiology · doi:10.1093/aje/kwy248 · Cited by 44 · see citing works
Rotem, R. S., Nguyen, V. T., Chodick, G., Davidovitch, M., Shalev, V., Hauser, R. B., Coull, B. A., Bellavia, A., & Weisskopf, M. G. (2020) · American Journal of Epidemiology · doi:10.1093/aje/kwaa219 · Cited by 44 · see citing works
Mediation analysis for survival data with high-dimensional mediators
Zhang, H., Zheng, Y., Hou, L., Zheng, C., & Liu, L. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab564 · Cited by 44 · see citing works
- Authors
- VanderWeele, T., & Vansteelandt, S.
- Affiliations
- Harvard University (US)
- Ghent University (BE)
- Corresponding author
- VanderWeele, Tyler
- Venue
- Epidemiologic Methods
- Publisher
- Walter de Gruyter GmbH
- Published
- 2014-01-03
- Volume
- 2
- Issue
- 1
- Pages
- 95-115
- ISSN
- 2161-962X (ISSN-L)
- 2194-9263
- PMC
- PMC4287269
- OpenAlex
- W2009754435
- Cited by
- 858
- References
- 23
- Citations by year
- 2026: 62 · 2025: 96 · 2024: 140 · 2023: 97 · 2022: 106 · 2021: 95 · 2020: 85 · 2019: 64 · 2018: 40 · 2017: 39 · 2016: 16 · 2015: 13 · 2014: 4
- FWCI
- 25.37
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Epidemiologic Methods (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion)
- Funders
- National Institute of Environmental Health Sciences (R01ES017876)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Keywords
- mediation analysis, multiple mediators, direct and indirect effects, count outcomes, causal inference, regression estimation
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
