The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Implementation of G-Computation on a Simulated Data Set: Demonstration of a Causal Inference Technique
Open accessAbstract
The growing body of work in the epidemiology literature focused on G-computation includes theoretical explanations of the method but very few simulations or examples of application. The small number of G-computation analyses in the epidemiology literature relative to other causal inference approaches may be partially due to a lack of didactic explanations of the method targeted toward an epidemiology audience. The authors provide a step-by-step demonstration of G-computation that is intended to familiarize the reader with this procedure. The authors simulate a data set and then demonstrate both G-computation and traditional regression to draw connections and illustrate contrasts between their implementation and interpretation relative to the truth of the simulation protocol. A marginal structural model is used for effect estimation in the G-computation example. The authors conclude by answering a series of questions to emphasize the key characteristics of causal inference techniques and the G-computation procedure in particular.
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Cites
Causality: Models, Reasoning, and Inference
Pearl, J. (2009) · doi:10.1017/cbo9780511803161 · Cited by 11,653
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
Constructing Inverse Probability Weights for Marginal Structural Models
Cole, S. R., & Hernan, M. A. (2008) · American Journal of Epidemiology · doi:10.1093/aje/kwn164 · Cited by 2,796
Robins, J. (1986) · Mathematical Modelling · doi:10.1016/0270-0255(86)90088-6 · Cited by 2,451
van der Laan, M. J., Polley, E. C., & Hubbard, A. E. (2007) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1309 · Cited by 1,719
Estimating causal effects from epidemiological data
Hernán, M. A., & Robins, J. M. (2006) · Journal of Epidemiology and Community Health · doi:10.1136/jech.2004.029496 · Cited by 1,028
Unified Methods for Censored Longitudinal Data and Causality
van der Laan, M. J., & Robins, J. M. (2003) · Springer Series in Statistics · doi:10.1007/978-0-387-21700-0 · Cited by 959
Targeted Maximum Likelihood Learning
van der Laan, M. J., & Rubin, D. (2006) · The International Journal of Biostatistics · doi:10.2202/1557-4679.1043 · Cited by 823
A definition of causal effect for epidemiological research
Hernán, M. A. (2004) · Journal of Epidemiology and Community Health · doi:10.1136/jech.2002.006361 · Cited by 462
Association, Causation, And Marginal Structural Models
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Cited by
Muller, C. J., & MacLehose, R. F. (2014) · International Journal of Epidemiology · doi:10.1093/ije/dyu029 · Cited by 775
Should multiple imputation be the method of choice for handling missing data in randomized trials?
Sullivan, T. R., White, I. R., Salter, A. B., Ryan, P., & Lee, K. J. (2018) · Statistical Methods in Medical Research · doi:10.1177/0962280216683570 · Cited by 308
Mortality Risk Score Prediction in an Elderly Population Using Machine Learning
Rose, S. (2013) · American Journal of Epidemiology · doi:10.1093/aje/kws241 · Cited by 193
Self-citationPlanning a method for covariate adjustment in individually randomised trials: a practical guide
Morris, T. P., Walker, A. S., Williamson, E. J., & White, I. R. (2022) · Trials · doi:10.1186/s13063-022-06097-z · Cited by 97
Reflection on modern methods: when worlds collide—prediction, machine learning and causal inference
Blakely, T., Lynch, J., Simons, K., Bentley, R., & Rose, S. (2021) · International Journal of Epidemiology · doi:10.1093/ije/dyz132 · Cited by 98
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Metadata
- Authors
- Snowden, J. M., Rose, S., & Mortimer, K. M.
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-03-16
- Volume
- 173
- Issue
- 7
- Pages
- 731-738
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- OpenAlex
- W2138909292
- Cited by
- 511
- References
- 32
- FWCI
- 11.68
- Type
- journal article
- Language
- en
- Open access
- green
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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.
