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, 35:437-466.

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, 183:1145–1166.

Mathur, M. and VanderWeele, T.J. (2020). Sensitivity analyses for publication bias in meta-analyses. Journal of the Royal Statistical Society, Series C, 69:1091-1119.

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