References
- Bickel, P. J., Klaassen, C., Ritov, Y., and Wellner, J. (1993), Efficient and Adaptive Inference in Semiparametric Models, Baltimore: Johns Hopkins University Press.
- Robins, J. M. (2000), “Marginal Structural Models Versus Structural Nested Models as Tools for Causal Inference,” in Statistical Models in Epidemiology, the Environment, and Clinical Trials, eds. M. E. Halloran and D. Berry, New York: Springer, pp. 95–133.
- Robins, J. M., and Greenland, S. (1992), “Identifiability and Exchangeability for Direct and Indirect Effects,” Epidemiology, 3, 143–155. DOI: 10.1097/00001648-199203000-00013.
- Vansteelandt, S., and Joffe, M. (2014), “Structural Nested Models and g-Estimation: The Partially Realized Promise,” Statistical Science, 29, 707–731. DOI: 10.1214/14-STS493.
- Yang, S., and Lok, J. J. (2016), “A Goodness-of-Fit Test for Structural Nested Mean Models,” Biometrika, 103, 734–741. DOI: 10.1093/biomet/asw031.
- Yang, S., and Lok, J. J. (2018), “Sensitivity Analysis for Unmeasured Confounding in Coarse Structural Nested Mean Models,” Statistica Sinica, 28, 1703–1723.
- Zeng, D. (2004), “Estimating Marginal Survival Function by Adjusting for Dependent Censoring Using Many Covariates,” The Annals of Statistics, 32, 1533–1555. DOI: 10.1214/009053604000000508.
- Zeng, D., and Chen, Q. (2010), “Adjustment for Informative Missingness Using Auxiliary Information in Semiparametric Regression, Biometrics, 66, 115–122. DOI: 10.1111/j.1541-0420.2009.01231.x.