2022 Rousseeuw Prize for Statistics awarded

The King Baudouin Foundation has awarded the 2022 Rousseeuw Prize for Statistics to James Robins (Harvard University) and a team comprising Miguel Hernán (Harvard University), Thomas Richardson (University of Washington), Andrea Rotnitzky (Universidad Torcuato di Tella, Argentina) and Eric Tchetgen Tchetgen (University of Pennsylvania) for their pioneering work on Causal Inference with applications in Medicine and Public Health. The biennial prize is worth $1 million.

The prize will be awarded at a ceremony taking place at KU Leuven on 12 October 2022.

Read a selection of articles written by the winners of the Rousseeuw Prize published in Wiley journals:

Robins, J.M. (1998), Correction for non-compliance in equivalence trials. Statist. Med., 17: 269-302. https://doi.org/10.1002/(SICI)1097-0258(19980215)17:3<269::AID-SIM763>3.0.CO;2-J

Brumback, B.A., Hernán, M.A., Haneuse, S.J.P.A. and Robins, J.M. (2004), Sensitivity analyses for unmeasured confounding assuming a marginal structural model for repeated measures. Statist. Med., 23: 749-767. https://doi.org/10.1002/sim.1657

VanderWeele, T.J. and Robins, J.M. (2010), Signed directed acyclic graphs for causal inference. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 72: 111-127. https://doi.org/10.1111/j.1467-9868.2009.00728.x

Structural Nested Failure Time Models, Robins, J.M. (2014) StatsRef

Inverse Probability Weighting in Survival Analysis, Rotnitzky, A. and Robins, J.M. (2014) StatsRef

Wen, L., Hernán, M. A., & Robins, J. M. (2021). Multiply robust estimators of causal effects for survival outcomes. Scand J Statist, 125. https://doi.org/10.1111/sjos.12561
Wen, L, Young, JG, Robins, JM, Hernán, MA. Parametric g-formula implementations for causal survival analyses. Biometrics. 2021; 77: 740753. https://doi.org/10.1111/biom.13321
Wang, L., Meng, X., Richardson, T.S. and Robins, J.M. (2022) Coherent modeling of longitudinal causal effects on binary outcomes. Biometrics, 00, 1 13. https://doi.org/10.1111/biom.13687
Prague, M., Wang, R., Stephens, A., Tchetgen Tchetgen, E. and DeGruttola, V. (2016), Accounting for interactions and complex inter-subject dependency in estimating treatment effect in cluster-randomized trials with missing outcomes. Biom, 72: 1066-1077. https://doi.org/10.1111/biom.12519
Drton, M. and Richardson, T.S. (2008), Binary models for marginal independence. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 70: 287-309. https://doi.org/10.1111/j.1467-9868.2007.00636.x
Liu, L., Tchetgen Tchetgen, E. (2022) Regression-based negative control of homophily in dyadic peer effect analysis. Biometrics, 78 668678. https://doi.org/10.1111/biom.13483

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