Investigation of the structure and magnitude of time-varying uncontrolled confounding in simulated cohort data analyzed using g-computation.

Published in: International journal of epidemiology (2023)

Time-varying uncontrolled confounding has the potential to substantially impact observed effect estimates. Given the importance of longitudinal studies in advising public health, the impact of time-varying uncontrolled confounding warrants more recognition and evaluation using quantitative bias analysis.

Keyphrases

public health
high resolution
cross sectional
machine learning
risk assessment
climate change
data analysis