Confounding adjustment methods in longitudinal observational data with a time-varying treatment: a mapping review.

Stan R W Wijn Maroeska M RoversGerjon Hannink

Published in: BMJ open (2022)

PSM is the most frequently used method to correct for confounding in longitudinal observational data. In studies with a time-varying treatment, PSM was potentially inappropriately used in 25% of studies. Confounding adjustment methods designed to deal with a time-varying treatment and time-varying confounding are available, but were only used in 45% of the studies with a time-varying treatment.

Keyphrases

electronic health record
machine learning
deep learning
data analysis
high density