Publications and Research

Investigación (Research)


Áreas de investigación: inferencia causal, datos faltantes, teoría semiparametrica, estadística no-paramétrica

Research areas: Causal Inference, Missing Data Analysis, Semiparametric Theory, Non-parametric Statistics



Algunas publicaciones recientes (Some recent publications)


1.      Babino, L., Rotnitzky, A. y Robins, J. (2019). Multiple robust estimation of marginal structural models for unconstrained outcomes. Biometrics. Vol 75-1, pp. 90-99

2.      Rotnitzky, A., Smucler, E. (2020). Efficient Adjustment Sets for Population Average Causal Treatment Effect Estimation in Graphical Models. Journal of Machine Learning Research. 21(188):1−86

3.      Rotnitzky, A., Smucler, E. y Robins, J. (2021). Characterization of parameters with a mixed bias property. Biometrika. Vol 108, 1, pp 231–238

4.      Liu, L., Shahn, Z., Robins, J., Rotnitzky, A. (2021) Efficient estimation of optimal regimes under a no direct effect assumption. Journal of the American Statistical Association. 116 (533), 224-239.

5.      Smucler, E., Sapienza, F. and Rotnitzky, A. (2022). Efficient adjustment sets in causal graphical models with hidden variables. Biometrika. Vol 109, 1, pp 49–65.

6.      Smucler, E. and Rotnitzky, A. (2022) A note on efficient minimum cost adjustment sets in causal graphical models.

7.      Guo, R., Perkovic, E. and Rotnitzky, A. (2022). Variable elimination, graph reduction and efficient g-formula.