The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Methods for dealing with time‐dependent confounding
Abstract
Longitudinal studies, where data are repeatedly collected on subjects over a period, are common in medical research. When estimating the effect of a time‐varying treatment or exposure on an outcome of interest measured at a later time, standard methods fail to give consistent estimators in the presence of time‐varying confounders if those confounders are themselves affected by the treatment. Robins and colleagues have proposed several alternative methods that, provided certain assumptions hold, avoid the problems associated with standard approaches. They include the g‐computation formula, inverse probability weighted estimation of marginal structural models and g‐estimation of structural nested models. In this tutorial, we give a description of each of these methods, exploring the links and differences between them and the reasons for choosing one over the others in different settings. Copyright © 2012 John Wiley & Sons, Ltd.
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Cites
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Marginal Structural Models and Causal Inference in Epidemiology
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Causal Diagrams for Epidemiologic Research
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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 · cited 2×
“[14] call collider-stratification bias.”
BackgroundRobins, J. (1986) · Mathematical Modelling · doi:10.1016/0270-0255(86)90088-6 · Cited by 2,451
The interpretation of interaction in contingency tables
Simpson, E. H. (1951) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1951.tb00088.x · Cited by 2,301 · cited 1×
“Because of the non-collapsibility of the odds ratio [24,25], it is not possible for P.”
BackgroundConfounding and Collapsibility in Causal Inference
Greenland, S., Pearl, J., & Robins, J. M. (1999) · Statistical Science · doi:10.1214/ss/1009211805 · Cited by 933 · cited 1×
“Because of the non-collapsibility of the odds ratio [24,25], it is not possible for P.”
BackgroundOrellana, L., Rotnitzky, A., & Robins, J. M. (2010) · The International Journal of Biostatistics · doi:10.2202/1557-4679.1200 · Cited by 202
On model selection and model misspecification in causal inference.
Vansteelandt, S., Bekaert, M., & Claeskens, G. (2012) · Statistical Methods in Medical Research · doi:10.1177/0962280210387717 · Cited by 172
A review of causal estimation of effects in mediation analyses
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A conceptual framework for the neurobiological study of resilience
Kalisch, R., Müller, M. B., & Tüscher, O. (2015) · Behavioral and Brain Sciences · doi:10.1017/s0140525x1400082x · Cited by 669
Naimi, A. I., Cole, S. R., & Kennedy, E. H. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw323 · Cited by 332
Weuve, J., Proust‐Lima, C., Power, M. C., Gross, A. L., Hofer, S. M., Thiébaut, R., Chêne, G., Glymour, M. M., Dufouil, C., & Initiative, M. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2015.06.1885 · Cited by 243
Analysis of randomised trials with long-term follow-up
Herbert, R. D., Kasza, J., & Bø, K. (2018) · BMC Medical Research Methodology · doi:10.1186/s12874-018-0499-5 · Cited by 80
Analyzing Patient Trajectories With Artificial Intelligence
Allam, A., Feuerriegel, S., Rebhan, M., & Krauthammer, M. (2021) · Journal of Medical Internet Research · doi:10.2196/29812 · Cited by 77
Understanding Marginal Structural Models for Time-Varying Exposures: Pitfalls and Tips
Shinozaki, T., & Suzuki, E. (2020) · Journal of Epidemiology · doi:10.2188/jea.je20200226 · Cited by 44
Inoue, K., Goto, A., Sugiyama, T., Ramlau-Hansen, C. H., & Liew, Z. (2020) · Toxics · doi:10.3390/toxics8040125 · Cited by 35
Bijlsma, M. J., & Wilson, B. (2020) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/rssa.12520 · Cited by 21
Metadata
- Authors
- Daniel, R. M., Cousens, S. N., De Stavola, B. L., Kenward, M. G., & Sterne, J. A. C.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2012-12-03
- Volume
- 32
- Issue
- 9
- Pages
- 1584-1618
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2159198921
- Cited by
- 376
- References
- 10
- FWCI
- 11.09
- Type
- journal article
- Language
- en
- Open access
- closed
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