03: Enhancing Causal Inference: The Comparison of Stratification Over Adjustment in IPTW Analyses

Music City Center 

Inverse Probability of Treatment Weighting (IPTW) is a key method in causal inference for estimating treatment effects while addressing confounding. While both stratification and adjustment are used to control for confounders, stratification may be superior when a confounder is strongly correlated with treatment. In this study, we emulated a target trial comparing surgical versus endovascular lower extremity revascularization for major adverse limb events. Given that chronic limb-threatening ischemia (CLTI) strongly influences treatment choice, we compared results between including the CLTI in the propensity score model and stratifying the data by CLTI and then running the propensity score model separately within the strata of CLTI. Our findings highlight the need for stratification when a confounder is strongly correlated with treatment.

Inverse Probability of Treatment Weighting (IPTW)

Causal Inference

Stratification

Adjustment 

Section on Statistical Consulting