Propensity score trimming mitigates bias due to covariate measurement error in inverse probability of treatment weighted analyses: A plasmode simulation

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Abstract

Differential misclassification of a strong predictor of exposure resulted in biased and imprecise IPTW estimates. Asymmetric trimming reduced bias, with more precise estimates than matching.

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Conover et al. (Tue,) studied this question.

synapsesocial.com/papers/69dbe05578a3e0e288685e1d https://doi.org/https://doi.org/10.1002/sim.8887

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