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.
Artículo
en Chino
| WPRIM
| ID: wpr-787699
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:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Tipo de estudio:
Estudio observacional
/
Estudio pronóstico
Idioma:
Chino
Revista:
Chinese Journal of Epidemiology
Año:
2020
Tipo del documento:
Artículo
Similares
MEDLINE
...
LILACS
LIS