Title
Analysis of Longitudinal Studies With Repeated Outcome Measures: Adjusting for Time-Dependent Confounding Using Conventional Methods
Analysis of Longitudinal Studies With Repeated Outcome Measures: Adjusting for Time-Dependent Confounding Using Conventional Methods
What is this about?
It shows how standard regression methods can be used, even in the presence of time-dependent confounding, to estimate the total effect of an exposure on a subsequent outcome by controlling appropriately for prior exposures, outcomes, and time-varying covariates.
It shows how standard regression methods can be used, even in the presence of time-dependent confounding, to estimate the total effect of an exposure on a subsequent outcome by controlling appropriately for prior exposures, outcomes, and time-varying covariates.
Type
Educational
Educational
Year
2018
2018
Domain
causal_inference_and_longitudinal_modelling
causal_inference_and_longitudinal_modelling
Reference
Am J Epidemiol. 2018 May 1;187(5):1085-1092.
Am J Epidemiol. 2018 May 1;187(5):1085-1092.
Keywords
direct effect, indirect effect, inverse probability weight, longitudinal study, marginal structural model, sequential conditional mean model, time-varying confounder, total effect
direct effect, indirect effect, inverse probability weight, longitudinal study, marginal structural model, sequential conditional mean model, time-varying confounder, total effect
Open access
Yes
Yes
Code
No
No
Lifecycle Tutorial
No
No
Not specified