A sequential conditional mean model for assessing total effects of exposure in longitudinal data / 中华流行病学杂志
Chinese Journal of Epidemiology
; (12): 111-114, 2020.
Article
en Zh
| WPRIM
| ID: wpr-798891
Biblioteca responsable:
WPRO
ABSTRACT
In prospective cohort study, multi follow up is often necessary for study subjects, and the observed values are correlated with each other, usually resulting in time-dependent confounding. In this case, the data generally do not meet the application conditions of traditional multivariate regression analysis. Sequential conditional mean model (SCMM) is a new approach that can deal with time-dependent confounding. This paper mainly summarizes the basic theory, steps and characteristics of SCMM.
Texto completo:
1
Base de datos:
WPRIM
Tipo de estudio:
Observational_studies
/
Prognostic_studies
Idioma:
Zh
Revista:
Chinese Journal of Epidemiology
Año:
2020
Tipo del documento:
Article