The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Estimation of the causal effects of time-varying exposures
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Citations
Cites
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Marginal Structural Models and Causal Inference in Epidemiology
Robins, J. M., Hernán, M. Á., & Brumback, B. (2000) · Epidemiology · doi:10.1097/00001648-200009000-00011 · Cited by 5,581
Self-citationCausation, Prediction, and Search
Spirtes, P., Glymour, C., & Scheines, R. (1993) · Lecture Notes in Statistics · doi:10.1007/978-1-4612-2748-9 · Cited by 4,617
A structural approach to selection bias
Hernán, M. A., Hernández-Díaz, S., & Robins, J. M. (2004) · Epidemiology · doi:10.1097/01.ede.0000135174.63482.43 · Cited by 2,844
Self-citationRobins, J. (1986) · Mathematical Modelling · doi:10.1016/0270-0255(86)90088-6 · Cited by 2,451
Self-citationCausal diagrams for empirical research
PEARL, J. (1995) · Biometrika · doi:10.1093/biomet/82.4.669 · Cited by 2,355
Doubly robust estimation in missing data and causal inference models
Bang, H., & Robins, J. M. (2005) · Biometrics · doi:10.1111/j.1541-0420.2005.00377.x · Cited by 1,998
Self-citationAnalysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data
Robins, J. M., Rotnitzky, A., & Zhao, L. P. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476493 · Cited by 1,595
Self-citationOptimal Dynamic Treatment Regimes
Murphy, S. A. (2003) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00389 · Cited by 1,007
Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models
Scharfstein, D. O., Rotnitzky, A., & Robins, J. M. (1999) · Journal of the American Statistical Association · doi:10.1080/01621459.1999.10473862 · Cited by 995
Self-citation
Cited by
Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available: Table 1.
Hernán, M. A., & Robins, J. M. (2016) · American Journal of Epidemiology · doi:10.1093/aje/kwv254 · Cited by 3,115
Self-citationPer-Protocol Analyses of Pragmatic Trials
Hernán, M. A., & Robins, J. M. (2017) · New England Journal of Medicine · doi:10.1056/nejmsm1605385 · Cited by 660
Self-citationCausal inference and counterfactual prediction in machine learning for actionable healthcare
Prosperi, M., Guo, Y., Sperrin, M., Koopman, J. S., Min, J. S., He, X., Rich, S., Wang, M., Buchan, I. E., & Bian, J. (2020) · Nature Machine Intelligence · doi:10.1038/s42256-020-0197-y · Cited by 459
Does obesity shorten life? The importance of well-defined interventions to answer causal questions
Hernán, M. A., & Taubman, S. L. (2008) · International Journal of Obesity · doi:10.1038/ijo.2008.82 · Cited by 384
Self-citationNaimi, A. I., Cole, S. R., & Kennedy, E. H. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw323 · Cited by 332
Metadata
- Authors
- Robins, J., & Hernan, M.
- Venue
- Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Publisher
- Chapman and Hall/CRC
- Published
- 2008-08-11
- Pages
- 553-599
- ISSN
- 2154-5944 (ISSN-L)
- OpenAlex
- W2496321160
- Cited by
- 312
- References
- 27
- FWCI
- 17.06
- Type
- book chapter
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Estimation of the causal effects of time-varying exposures. https://app.cochat.ai/papers/10.1201/9781420011579.ch23
- The paper
- Robins, J., & Hernan, M. (2008). Estimation of the causal effects of time-varying exposures. Chapman & Hall/CRC Handbooks of Modern Statistical Methods. https://doi.org/10.1201/9781420011579.ch23
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
