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| Titre : | Comparison of population-averaged and subject-specific approaches for analysing repeated binary outcomes (1998) |
| Auteurs : | Frank B. Hu ; Jack Goldberg ; Donald Hedeker ; Brian R. Flay ; Mary Ann Pentz |
| Type de document : | Article : document électronique |
| Dans : | American Journal of Epidemiology (Volume 147, n° 7, April 1998) |
| Article en page(s) : | pp. 694-703 |
| Langues: | Anglais |
| Catégories : |
Thésaurus CEREQ ANALYSE DES DONNEES ; EVALUATION ; METHODOLOGIE D'ENQUETE ; ENQUETE LONGITUDINALE ; MODELISATION |
| Résumé : | Several approaches have been proposed to model binary outcomes that arise from longitudinal studies. Most of the approaches can be grouped into two classes: the population-averaged and subject-specific approaches. The generalized estimating equations (GEE) method is commonly used to estimate population-averaged effects, while random-effects logistic models can be used to estimate subject-specific effects. However, it is not clear to many epidemiologists how these two methods relate to one another or how these methods relate to more traditional stratified analysis and standard logistic models. The authors address these issues in the context of a longitudinal smoking prevention trial, the Midwestern Prevention Project. In particular, the authors compare results from stratified analysis, standard logistic models, conditional logistic models, the GEE models, and random-effects models by analyzing a binary outcome from two and seven repeated measurements, respectively. In the comparison, the authors focus on the interpretation of both time-varying and time-invariant covariates under different models. Implications of these methods for epidemiologic research are discussed. |
| Document Céreq : | Non |
| En ligne : | https://doi.org/10.1093/oxfordjournals.aje.a009511 |
Documents numériques (1)
 147-7-694.pdf Adobe Acrobat PDF |
