Romain S. Neugebauer, Ph.D.

Affiliations: 
2004 University of California, Berkeley, Berkeley, CA, United States 
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"Romain Neugebauer"

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Mark J. van der Laan grad student 2004 UC Berkeley
 (Double robust estimation of causal parameters in marginal structural models.)
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Publications

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Williamson BD, Wyss R, Stuart EA, et al. (2023) An application of the Causal Roadmap in two safety monitoring case studies: Causal inference and outcome prediction using electronic health record data. Journal of Clinical and Translational Science. 7: e208
Kreif N, Sofrygin O, Schmittdiel JA, et al. (2020) Exploiting non-systematic covariate monitoring to broaden the scope of evidence about the causal effects of adaptive treatment strategies. Biometrics
Sofrygin O, Zhu Z, Schmittdiel JA, et al. (2019) Targeted learning with daily EHR data. Statistics in Medicine
Neugebauer R, Schmittdiel JA, Adams AS, et al. (2017) Identification of the joint effect of a dynamic treatment intervention and a stochastic monitoring intervention under the no direct effect assumption. Journal of Causal Inference. 5
Sofrygin O, van der Laan MJ, Neugebauer R. (2017) simcausal R Package: Conducting Transparent and Reproducible Simulation Studies of Causal Effect Estimation with Complex Longitudinal Data. Journal of Statistical Software. 81
Neugebauer R, Schmittdiel JA, van der Laan MJ. (2016) A Case Study of the Impact of Data-Adaptive Versus Model-Based Estimation of the Propensity Scores on Causal Inferences from Three Inverse Probability Weighting Estimators. The International Journal of Biostatistics. 12: 131-55
Raine-Bennett T, Tucker LY, Zaritsky E, et al. (2015) Occult Uterine Sarcoma and Leiomyosarcoma: Incidence of and Survival Associated With Morcellation. Obstetrics and Gynecology
Neugebauer R, Schmittdiel JA, Zhu Z, et al. (2015) High-dimensional propensity score algorithm in comparative effectiveness research with time-varying interventions. Statistics in Medicine. 34: 753-81
Neugebauer R, Schmittdiel JA, van der Laan MJ. (2014) Targeted learning in real-world comparative effectiveness research with time-varying interventions. Statistics in Medicine. 33: 2480-520
Neugebauer R, Fireman B, Roy JA, et al. (2013) Super learning to hedge against incorrect inference from arbitrary parametric assumptions in marginal structural modeling. Journal of Clinical Epidemiology. 66: S99-109
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