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
in Chinese
| 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.
Full text:
Available
Index:
WPRIM (Western Pacific)
Type of study:
Observational study
/
Prognostic study
Language:
Chinese
Journal:
Chinese Journal of Epidemiology
Year:
2020
Type:
Article
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