| Titre : | Constructing Inverse Probability Weights for Marginal Structural Models. (2008) |
| Auteurs : | COLE (Stephen-R) : USA. Department of Epidemiology. Johns Hopkins Bloomberg School of Public Health. Baltimore. MD. ; HERNAN (Miguel-A) : USA. Department of Epidemiology. Harvard School of Public Health. Boston. MA. |
| Type de document : | Article |
| Dans : | American journal of epidemiology (vol. 168, n° 6, 2008) |
| Pagination : | 656-664 |
| Langues: | Anglais |
| Mots-clés : | Probabilité ; Biais ; Epidémiologie ; Homme |
| Résumé : | [BDSP. Notice produite par INIST-CNRS 9oR0xpA7. Diffusion soumise à autorisation]. The method of inverse probability weighting (henceforth, weighting) can be used to adjust for measured confounding and selection bias under the four assumptions of consistency, exchangeability, positivity, and no mis-specification of the model used to estimate weights. In recent years, several published estimates of the effect of time-varying exposures have been based on weighted estimation of the parameters of marginal structural models because, unlike standard statistical methods, weighting can appropriately adjust for measured time-varying confounders affected by prior exposure. As an example, the authors describe the last three assumptions using the change in viral load due to initiation of antiretroviral therapy among 918 human immunodeficiency virus-infected US men and women followed for a median of 5.8 years between 1996 and 2005. The authors describe possible tradeoffs that an epidemiologist may encounter when attempting to make inferences. For instance, a trade off between bias and precision is illustrated as a function of the extent to which confounding is controlled. Weight truncation is presented as an informal and easily implemented method to deal with these trade offs. Inverse probability weighting provides a powerful methodological tool that may uncover causal effects of exposures that are otherwise obscured. However, as with all methods, diagnostics and sensitivity analyses are essential for proper use. |
Service Documentation EHESP
Me connecter
PORTAIL DOCUMENTAIRE
École des hautes études en santé publique
Catalogue
Multi-bases
Accueil
Sélection de la langue
Adresse
Service Documentation EHESPBibliothèque Rennes Avenue du Professeur Léon Bernard – CS 74312 – 35043 Rennes Cedex Bibliothèque MSSH Paris 20 avenue George Sand - 93210 La Plaine Saint-Denis
France
Bibliothèque Rennes : 02 99 02 29 50 Bibliothèque MSSH Paris : 02 99 02 24 50
contact