Superfund Research Program
Data Management and Analysis Core (DMAC)
Project Leader: Alan E. Hubbard
Co-Investigator: Andres Cardenas (Stanford University)
Grant Number: P42ES004705
Funding Period: 2022-2027
Project-Specific Links
- Project Summary
Publications
2023
- Hejazi NS, Boileau P, van der Laan MJ, Hubbard AE. 2023. A generalization of moderated statistics to data adaptive semiparametric estimation in high-dimensional biology. Stat Methods Med Res 32(3):539-554. doi:10.1177/09622802221146313 PMID:36573044
- McCoy D, Hubbard AE, van der Laan MJ. 2023. CVtreeMLE: efficient estimation of mixed exposures using data adaptive decision trees and cross-validated targeted maximum likelihood estimation in R. J Open Source Softw 8(82):4181. doi:10.21105/joss.04181 PMID:37398941 PMCID:PMC10312067
- McCoy D, Schuler A, Hubbard AE, van der Laan MJ. 2023. SuperNOVA: semi-parametric identification and estimation of interaction and effect modification in mixed exposure using stochastic interventions in R. J Open Source Softw 8(91):5422. doi:10.21105/joss.05422
2022
- Germolec DR, Lebrec H, Anderson SE, Burleson GR, Cardenas A, Corsini E, Elmore S, Kaplan BL, Lawrence BP, Lehmann GM, Maier CC, McHale CM, Myers LP, Pallardy M, Rooney AA, Zeise L, Zhang L, Smith MT. 2022. Consensus on the key characteristics of immunotoxic agents as a basis for hazard identification. Environ Health Perspect 130(10):105001. doi:10.1289/EHP10800 PMID:36201310 PMCID:PMC9536493