| Titre : | Implementation of G-Computation on a Simulated Data Set : Demonstration of a Causal Inference Technique. (2011) |
| Auteurs : | Jonathan-M SNOWDEN ; Kathleen-M MORTIMER ; ROSE (Sherri) : USA. Division of Biostatistics. School of Public Health. University of California. Berkeley. Berkeley. CA. |
| Type de document : | Article |
| Dans : | American journal of epidemiology (vol. 173, n° 7, 2011) |
| Pagination : | 731-738 |
| Langues: | Anglais |
| Mots-clés : | Asthme ; Technique simulation ; Simulation ; Facteur ; Pollution atmosphérique ; Santé environnementale ; Méthode ; Méthodologie ; Epidémiologie ; Bronchopneumopathie obstructive |
| Résumé : | [BDSP. Notice produite par INIST-CNRS 88R0xGsn. Diffusion soumise à autorisation]. 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. |
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