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On the definition of a confounder.

Annals of statistics

VanderWeele TJ, Shpitser I.
PMID: 25544784
Ann Stat. 2013 Feb;41(1):196-220. doi: 10.1214/12-aos1058.

The causal inference literature has provided a clear formal definition of confounding expressed in terms of counterfactual independence. The causal inference literature has not, however, produced a clear formal definition of a confounder, as it has given priority to...

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VanderWeele TJ, Shpitser I. On the definition of a confounder. Ann Stat. 2013;41(1):196-220doi: 10.1214/12-aos1058.
VanderWeele, T. J., & Shpitser, I. (2013). On the definition of a confounder. Annals of statistics, 41(1), 196-220. https://doi.org/10.1214/12-aos1058
VanderWeele, Tyler J, and Shpitser, Ilya. "On the definition of a confounder." Annals of statistics vol. 41,1 (2013): 196-220. doi: https://doi.org/10.1214/12-aos1058
VanderWeele TJ, Shpitser I. On the definition of a confounder. Ann Stat. 2013 Feb;41(1):196-220. doi: 10.1214/12-aos1058. PMID: 25544784; PMCID: PMC4276366.
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Sensitivity analysis for direct and indirect effects in the presence of exposure-induced mediator-outcome confounders.

Epidemiology, biostatistics and public health

VanderWeele TJ, Chiba Y.
PMID: 25580387
Epidemiol Biostat Public Health. 2014;11(2). doi: 10.2427/9027.

Questions of mediation are often of interest in reasoning about mechanisms, and methods have been developed to address these questions. However, these methods make strong assumptions about the absence of confounding. Even if exposure is randomized, there may be...

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VanderWeele TJ, Chiba Y. Sensitivity analysis for direct and indirect effects in the presence of exposure-induced mediator-outcome confounders. Epidemiol Biostat Public Health. 2014;11(2)doi: 10.2427/9027.
VanderWeele, T. J., & Chiba, Y. (2014). Sensitivity analysis for direct and indirect effects in the presence of exposure-induced mediator-outcome confounders. Epidemiology, biostatistics and public health, 11(2), . https://doi.org/10.2427/9027
VanderWeele, Tyler J, and Chiba, Yasutaka. "Sensitivity analysis for direct and indirect effects in the presence of exposure-induced mediator-outcome confounders." Epidemiology, biostatistics and public health vol. 11,2 (2014). doi: https://doi.org/10.2427/9027
VanderWeele TJ, Chiba Y. Sensitivity analysis for direct and indirect effects in the presence of exposure-induced mediator-outcome confounders. Epidemiol Biostat Public Health. 2014;11(2). doi: 10.2427/9027. PMID: 25580387; PMCID: PMC4287391.
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Sensitivity analysis for contagion effects in social networks.

Sociological methods & research

VanderWeele TJ.
PMID: 25580037
Sociol Methods Res. 2011 May;40(2):240-255. doi: 10.1177/0049124111404821.

Analyses of social network data have suggested that obesity, smoking, happiness and loneliness all travel through social networks. Individuals exert "contagion effects" on one another through social ties and association. These analyses have come under critique because of the...

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VanderWeele TJ. Sensitivity analysis for contagion effects in social networks. Sociol Methods Res. 2011;40(2):240-255doi: 10.1177/0049124111404821.
VanderWeele, T. J. (2011). Sensitivity analysis for contagion effects in social networks. Sociological methods & research, 40(2), 240-255. https://doi.org/10.1177/0049124111404821
VanderWeele, Tyler J. "Sensitivity analysis for contagion effects in social networks." Sociological methods & research vol. 40,2 (2011): 240-255. doi: https://doi.org/10.1177/0049124111404821
VanderWeele TJ. Sensitivity analysis for contagion effects in social networks. Sociol Methods Res. 2011 May;40(2):240-255. doi: 10.1177/0049124111404821. PMID: 25580037; PMCID: PMC4288024.
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Author's reply: The role of potential outcomes thinking in assessing mediation and interaction.

International journal of epidemiology

VanderWeele TJ.
PMID: 27864414
Int J Epidemiol. 2016 Dec 01;45(6):1922-1926. doi: 10.1093/ije/dyw280.

No abstract available.

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VanderWeele TJ. Author's reply: The role of potential outcomes thinking in assessing mediation and interaction. Int J Epidemiol. 2016;45(6):1922-1926doi: 10.1093/ije/dyw280.
VanderWeele, T. J. (2016). Author's reply: The role of potential outcomes thinking in assessing mediation and interaction. International journal of epidemiology, 45(6), 1922-1926. https://doi.org/10.1093/ije/dyw280
VanderWeele, Tyler J. "Author's reply: The role of potential outcomes thinking in assessing mediation and interaction." International journal of epidemiology vol. 45,6 (2016): 1922-1926. doi: https://doi.org/10.1093/ije/dyw280
VanderWeele TJ. Author's reply: The role of potential outcomes thinking in assessing mediation and interaction. Int J Epidemiol. 2016 Dec 01;45(6):1922-1926. doi: 10.1093/ije/dyw280. PMID: 27864414; PMCID: PMC5841620.
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Identification and Estimation of Causal Mechanisms in Clustered Encouragement Designs: Disentangling Bed Nets using Bayesian Principal Stratification.

Journal of the American Statistical Association

Forastiere L, Mealli F, VanderWeele TJ.
PMID: 28008210
J Am Stat Assoc. 2016;111(514):510-525. doi: 10.1080/01621459.2015.1125788. Epub 2016 Aug 18.

Exploration of causal mechanisms is often important for researchers and policymakers to understand how an intervention works and how it can be improved. This task can be crucial in clustered encouragement designs (CED). Encouragement design studies arise frequently when...

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Forastiere L, Mealli F, VanderWeele TJ. Identification and Estimation of Causal Mechanisms in Clustered Encouragement Designs: Disentangling Bed Nets using Bayesian Principal Stratification. J Am Stat Assoc. 2016;111(514):510-525doi: 10.1080/01621459.2015.1125788.
Forastiere, L., Mealli, F., & VanderWeele, T. J. (2016). Identification and Estimation of Causal Mechanisms in Clustered Encouragement Designs: Disentangling Bed Nets using Bayesian Principal Stratification. Journal of the American Statistical Association, 111(514), 510-525. https://doi.org/10.1080/01621459.2015.1125788
Forastiere, Laura, et al. "Identification and Estimation of Causal Mechanisms in Clustered Encouragement Designs: Disentangling Bed Nets using Bayesian Principal Stratification." Journal of the American Statistical Association vol. 111,514 (2016): 510-525. doi: https://doi.org/10.1080/01621459.2015.1125788
Forastiere L, Mealli F, VanderWeele TJ. Identification and Estimation of Causal Mechanisms in Clustered Encouragement Designs: Disentangling Bed Nets using Bayesian Principal Stratification. J Am Stat Assoc. 2016;111(514):510-525. doi: 10.1080/01621459.2015.1125788. Epub 2016 Aug 18. PMID: 28008210; PMCID: PMC5166715.
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Commentary: On Causes, Causal Inference, and Potential Outcomes.

International journal of epidemiology

VanderWeele TJ.
PMID: 28130319
Int J Epidemiol. 2016 Dec 01;45(6):1809-1816. doi: 10.1093/ije/dyw230.

No abstract available.

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VanderWeele TJ. Commentary: On Causes, Causal Inference, and Potential Outcomes. Int J Epidemiol. 2016;45(6):1809-1816doi: 10.1093/ije/dyw230.
VanderWeele, T. J. (2016). Commentary: On Causes, Causal Inference, and Potential Outcomes. International journal of epidemiology, 45(6), 1809-1816. https://doi.org/10.1093/ije/dyw230
VanderWeele, Tyler J. "Commentary: On Causes, Causal Inference, and Potential Outcomes." International journal of epidemiology vol. 45,6 (2016): 1809-1816. doi: https://doi.org/10.1093/ije/dyw230
VanderWeele TJ. Commentary: On Causes, Causal Inference, and Potential Outcomes. Int J Epidemiol. 2016 Dec 01;45(6):1809-1816. doi: 10.1093/ije/dyw230. PMID: 28130319; PMCID: PMC5841618.
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Mediation analysis with time varying exposures and mediators.

Journal of the Royal Statistical Society. Series B, Statistical methodology

VanderWeele TJ, Tchetgen Tchetgen EJ.
PMID: 28824285
J R Stat Soc Series B Stat Methodol. 2017 Jun;79(3):917-938. doi: 10.1111/rssb.12194. Epub 2016 Jun 27.

In this paper we consider causal mediation analysis when exposures and mediators vary over time. We give non-parametric identification results, discuss parametric implementation, and also provide a weighting approach to direct and indirect effects based on combining the results...

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VanderWeele TJ, Tchetgen Tchetgen EJ. Mediation analysis with time varying exposures and mediators. J R Stat Soc Series B Stat Methodol. 2016;79(3):917-938doi: 10.1111/rssb.12194.
VanderWeele, T. J., & Tchetgen Tchetgen, E. J. (2017). Mediation analysis with time varying exposures and mediators. Journal of the Royal Statistical Society. Series B, Statistical methodology, 79(3), 917-938. https://doi.org/10.1111/rssb.12194
VanderWeele, Tyler J, and Tchetgen Tchetgen, Eric J. "Mediation analysis with time varying exposures and mediators." Journal of the Royal Statistical Society. Series B, Statistical methodology vol. 79,3 (2017): 917-938. doi: https://doi.org/10.1111/rssb.12194
VanderWeele TJ, Tchetgen Tchetgen EJ. Mediation analysis with time varying exposures and mediators. J R Stat Soc Series B Stat Methodol. 2017 Jun;79(3):917-938. doi: 10.1111/rssb.12194. Epub 2016 Jun 27. PMID: 28824285; PMCID: PMC5560424.
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Mediation and spillover effects in group-randomized trials: a case study of the 4Rs educational intervention.

Journal of the American Statistical Association

Vanderweele TJ, Hong G, Jones SM, Brown JL.
PMID: 23997375
J Am Stat Assoc. 2013 Jun 01;108(502):469-482. doi: 10.1080/01621459.2013.779832.

Peer influence and social interactions can give rise to spillover effects in which the exposure of one individual may affect outcomes of other individuals. Even if the intervention under study occurs at the group or cluster level as in...

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Vanderweele TJ, Hong G, Jones SM, et al. Mediation and spillover effects in group-randomized trials: a case study of the 4Rs educational intervention. J Am Stat Assoc. 2013;108(502):469-482doi: 10.1080/01621459.2013.779832.
Vanderweele, T. J., Hong, G., Jones, S. M., & Brown, J. L. (2013). Mediation and spillover effects in group-randomized trials: a case study of the 4Rs educational intervention. Journal of the American Statistical Association, 108(502), 469-482. https://doi.org/10.1080/01621459.2013.779832
Vanderweele, Tyler J, et al. "Mediation and spillover effects in group-randomized trials: a case study of the 4Rs educational intervention." Journal of the American Statistical Association vol. 108,502 (2013): 469-482. doi: https://doi.org/10.1080/01621459.2013.779832
Vanderweele TJ, Hong G, Jones SM, Brown JL. Mediation and spillover effects in group-randomized trials: a case study of the 4Rs educational intervention. J Am Stat Assoc. 2013 Jun 01;108(502):469-482. doi: 10.1080/01621459.2013.779832. PMID: 23997375; PMCID: PMC3753117.
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Monotone Confounding, Monotone Treatment Selection and Monotone Treatment Response.

Journal of causal inference

VanderWeele TJ, Jiang Z, Chiba Y.
PMID: 25574455
J Causal Inference. 2014 Mar;2(1):1-12. doi: 10.1515/jci-2012-0006.

Manski (1997) and Manski and Pepper (2000) gave sharp bounds on causal effects under the assumptions of monotone treatment response (MTR) and monotone treatment selection (MTS). VanderWeele (2008) provided bounds for binary treatment under an assumption of monotone confounding...

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VanderWeele TJ, Jiang Z, Chiba Y. Monotone Confounding, Monotone Treatment Selection and Monotone Treatment Response. J Causal Inference. 2014;2(1):1-12doi: 10.1515/jci-2012-0006.
VanderWeele, T. J., Jiang, Z., & Chiba, Y. (2014). Monotone Confounding, Monotone Treatment Selection and Monotone Treatment Response. Journal of causal inference, 2(1), 1-12. https://doi.org/10.1515/jci-2012-0006
VanderWeele, Tyler J, et al. "Monotone Confounding, Monotone Treatment Selection and Monotone Treatment Response." Journal of causal inference vol. 2,1 (2014): 1-12. doi: https://doi.org/10.1515/jci-2012-0006
VanderWeele TJ, Jiang Z, Chiba Y. Monotone Confounding, Monotone Treatment Selection and Monotone Treatment Response. J Causal Inference. 2014 Mar;2(1):1-12. doi: 10.1515/jci-2012-0006. PMID: 25574455; PMCID: PMC4283804.
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Semiparametric tests for sufficient cause interaction.

Journal of the Royal Statistical Society. Series B, Statistical methodology

Vansteelandt S, VanderWeele TJ, Robins JM.
PMID: 25558182
J R Stat Soc Series B Stat Methodol. 2012 Mar;74(2):223-244. doi: 10.1111/j.1467-9868.2011.01011.x.

A sufficient cause interaction between two exposures signals the presence of individuals for whom the outcome would occur only under certain values of the two exposures. When the outcome is dichotomous and all exposures are categorical, then under certain...

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Vansteelandt S, VanderWeele TJ, Robins JM. Semiparametric tests for sufficient cause interaction. J R Stat Soc Series B Stat Methodol. 2012;74(2):223-244doi: 10.1111/j.1467-9868.2011.01011.x.
Vansteelandt, S., VanderWeele, T. J., & Robins, J. M. (2012). Semiparametric tests for sufficient cause interaction. Journal of the Royal Statistical Society. Series B, Statistical methodology, 74(2), 223-244. https://doi.org/10.1111/j.1467-9868.2011.01011.x
Vansteelandt, Stijn, et al. "Semiparametric tests for sufficient cause interaction." Journal of the Royal Statistical Society. Series B, Statistical methodology vol. 74,2 (2012): 223-244. doi: https://doi.org/10.1111/j.1467-9868.2011.01011.x
Vansteelandt S, VanderWeele TJ, Robins JM. Semiparametric tests for sufficient cause interaction. J R Stat Soc Series B Stat Methodol. 2012 Mar;74(2):223-244. doi: 10.1111/j.1467-9868.2011.01011.x. PMID: 25558182; PMCID: PMC4280915.
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A proof of Bell's inequality in quantum mechanics using causal interactions.

Scandinavian journal of statistics, theory and applications

Robins JM, VanderWeele TJ, Gill RD.
PMID: 26236075
Scand Stat Theory Appl. 2015 Jun 01;42(2):329-335. doi: 10.1111/sjos.12089.

We give a simple proof of Bell's inequality in quantum mechanics using theory from causal interaction, which, in conjunction with experiments, demonstrates that the local hidden variables assumption is false. The proof sheds light on relationships between the notion...

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Robins JM, VanderWeele TJ, Gill RD. A proof of Bell's inequality in quantum mechanics using causal interactions. Scand Stat Theory Appl. 2015;42(2):329-335doi: 10.1111/sjos.12089.
Robins, J. M., VanderWeele, T. J., & Gill, R. D. (2015). A proof of Bell's inequality in quantum mechanics using causal interactions. Scandinavian journal of statistics, theory and applications, 42(2), 329-335. https://doi.org/10.1111/sjos.12089
Robins, James M, et al. "A proof of Bell's inequality in quantum mechanics using causal interactions." Scandinavian journal of statistics, theory and applications vol. 42,2 (2015): 329-335. doi: https://doi.org/10.1111/sjos.12089
Robins JM, VanderWeele TJ, Gill RD. A proof of Bell's inequality in quantum mechanics using causal interactions. Scand Stat Theory Appl. 2015 Jun 01;42(2):329-335. doi: 10.1111/sjos.12089. PMID: 26236075; PMCID: PMC4520697.
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Causal Inference Under Multiple Versions of Treatment.

Journal of causal inference

VanderWeele TJ, Hernán MA.
PMID: 25379365
J Causal Inference. 2013 May 01;1(1):1-20. doi: 10.1515/jci-2012-0002.

No abstract available.

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VanderWeele TJ, Hernán MA. Causal Inference Under Multiple Versions of Treatment. J Causal Inference. 2013;1(1):1-20doi: 10.1515/jci-2012-0002.
VanderWeele, T. J., & Hernán, M. A. (2013). Causal Inference Under Multiple Versions of Treatment. Journal of causal inference, 1(1), 1-20. https://doi.org/10.1515/jci-2012-0002
VanderWeele, Tyler J, and Hernán, Miguel A. "Causal Inference Under Multiple Versions of Treatment." Journal of causal inference vol. 1,1 (2013): 1-20. doi: https://doi.org/10.1515/jci-2012-0002
VanderWeele TJ, Hernán MA. Causal Inference Under Multiple Versions of Treatment. J Causal Inference. 2013 May 01;1(1):1-20. doi: 10.1515/jci-2012-0002. PMID: 25379365; PMCID: PMC4219328.
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Showing 1 to 12 of 30 entries