Selected Methodological Publications


Measurement for Psychosocial Constructs:

VanderWeele, T.J. (2020). Causal inference and constructed measures: towards a new model of measurement for psychosocial constructs. Technical Report.

VanderWeele, T.J. and Vansteelandt, S. (2020).  A statistical test to reject the structural interpretation of a latent factor model. Technical Report.

VanderWeele, T.J. and Batty, C.J.K. (2020). On the dimensional indeterminacy of one-wave factor analysis under causal effects. Technical Report.


Outcome-Wide Studies:

VanderWeele, T.J., Mathur, M.B., and Chen, Y. (2020). Outcome-wide longitudinal designs for causal inference: a new template for empirical studies. Statistical Science, in press.

VanderWeele, T.J. (2017). Outcome-wide epidemiology. Epidemiology, 28:399-402.


Confounding and Confounders:

VanderWeele, T.J. (2019). Principles of confounder selection. European Journal of Epidemiology, 34:211-219.

VanderWeele, T.J. and Shpitser, I. (2013). On the definition of a confounder. Annals of Statistics, 41:196-220.

VanderWeele, T.J. and Shpitser, I. (2011). A new criterion for confounder selection. Biometrics, 67:1406-1413.


Sensitivity Analysis:

Smith, L.H. and VanderWeele, T.J. (2019). Bounding bias due to selection. Epidemiology, 30:509-516.

VanderWeele, T.J. and Li, Y. (2019). Simple sensitivity analysis for differential measurement error. American Journal of Epidemiology, 10:1823-1829.

VanderWeele, T.J. and Ding, P. (2017). Sensitivity analysis in observational research: introducing the E-value. Annals of Internal Medicine, 167:268-274.


Meta-Analysis and Replication:

Mathur, M. and VanderWeele, T.J. (2020). New statistical metrics for multisite replication projects. Journal of the Royal Statistical Society, Series A, in press.

Mathur, M. and VanderWeele, T.J. (2020). Sensitivity analyses for publication bias in meta-analyses. Journal of the Royal Statistical Society, Series C, in press.

Mathur, M. and VanderWeele, T.J. (2020). Sensitivity analysis for unmeasured confounding in meta-analyses. Journal of the American Statistical Association, 115:163-172.

Mathur, M. and VanderWeele, T.J. (2019). New metrics for meta-analyses of heterogeneous effects. Statistics in Medicine, 3:1336-1342.


Mediation Analysis:

VanderWeele, T.J. and Tchetgen Tchetgen, E.J. (2017). Mediation analysis with time-varying exposures and mediators. Journal of the Royal Statistical Society, Series B, 79:917-938.

VanderWeele, T.J. (2015). Explanation in Causal Inference: Methods for Mediation and Interaction. New York: Oxford University Press.

VanderWeele, T.J. (2014). A unification of mediation and interaction: a four-way decomposition. Epidemiology, 25:749-761.

VanderWeele, T.J. (2013). Surrogate measures and consistent surrogates (with Discussion). Biometrics, 69:561-681.


Mendelian Randomization:

Swanson, S.A. and VanderWeele, T.J. (2020). E-values for Mendelian randomization. Epidemiology, 31:e23-e24.

VanderWeele, T.J., Tchetgen Tchetgen E.J., Cornelis, M., and Kraft, P. (2014). Methodological challenges in Mendelian randomization. Epidemiology, 25:427-435.


Methods for Racial Disparities:

Jackson, J.W. and VanderWeele, T.J. (2018). Decomposition analysis to identify intervention targets for reducing disparities. Epidemiology, 29:825-835.

Jackson, J.W., Williams, D.R., and VanderWeele, T.J. (2016). Disparities at the intersection of marginalized groups. Social Psychiatry and Psychiatric Epidemiology, 51:1349-1359.

VanderWeele, T.J. and Robinson, W.R. (2014). On the causal interpretation of race in regressions adjusting for confounding and mediating variables. Epidemiology, 25:473-484.



VanderWeele, T.J., Luedtke A.R., van der Laan, M.J., and Kessler, R.C. (2019). Selecting optimal subgroups for treatment using many covariates. Epidemiology, 30:334-341.

VanderWeele, T.J. (2019). The interaction continuum. Epidemiology, 30:648-658.

VanderWeele, T.J. and Richardson, T.S. (2012). General theory for interactions in sufficient cause models with dichotomous exposures. Annals of Statistics, 40:2128-2161.

VanderWeele, T.J. (2009). On the distinction between interaction and effect modification. Epidemiology, 20:863-871.


Social Networks:

VanderWeele, T.J. and Christakis, N.A. (2019). Network multipliers and public health. International Journal of Epidemiology, 48:1032-1037.

VanderWeele, T.J. and An, W. (2013). Social networks and causal inference. Handbook of Causal Analysis for Social Research, S.L. Morgan (ed.). Springer, Chapter 17, p. 353-374.

VanderWeele, T.J. (2011). Sensitivity analysis for contagion effects in social networks. Sociological Methods and Research, 40:240-255.


Spillover Effects:

VanderWeele, T.J., Hong, G., Jones, S. and Brown, J. (2013). Mediation and spillover effects in group-randomized trials: a case study of the 4R’s educational intervention. Journal of the American Statistical Association, 108:469-482.

VanderWeele, T.J., Vandenbroucke, J.P., Tchetgen Tchetgen, E.J., and Robins, J.M. (2012). A mapping between interactions and interference: implications for vaccine trials. Epidemiology, 23:285-292.

Tchetgen Tchetgen, E.J. and VanderWeele, T.J. (2012). On causal inference in the presence of interference. Statistical Methods in Medical Research – Special Issue on Causal Inference, 21:55-75.


Causal Diagrams:

Ogburn, E.L. and VanderWeele, T.J. (2014). Causal diagrams for interference and contagion. Statistical Science, 29:559-578.

VanderWeele, T.J. and Robins, J.M. (2010). Signed directed acyclic graphs for causal inference. Journal of the Royal Statistical Society, Series B, 72:111-127.

VanderWeele, T.J. and Robins, J.M. (2009). Minimal sufficient causation and directed acyclic graphs. Annals of Statistics, 37:1437-1465.


Multiple Versions of Treatment:

VanderWeele, T.J. (2018). On well-defined hypothetical interventions in the potential outcomes framework. Epidemiology, 29:e24–e25.

VanderWeele, T.J. (2016). On causes, causal inference, and potential outcomes. International Journal of Epidemiology, 45:1809-1816.

VanderWeele, T.J. and Hernán, M.A. (2013). Causal inference under multiple versions of treatment. Journal of Causal Inference, 1:1-20.


Link to: Substantive Research Publications
Link to: Methodological Research Publications