[Introduction to an individual-based standardization method -- propensity score weighting].
Zhiwen Li, Jianmeng Liu, Aiguo Ren
Abstract
Zhiwen Li, Jianmeng Liu, Aiguo Ren
Abstract
In this article, we presented the rationale and calculation procedures of a propensity score weighting method, with its application in epidemiological studies. The rationale for propensity score weighting method is similar to those for traditional standardization methods. Propensity score is used to estimate the weight for each individual. As the propensity score serves the function of observed covariates, the propensity score weighting can balance the distribution of the observed covariates between the comparison groups. There are two weighting methods according to the target standard populations: the Inverse probability of treatment weighting (IPTW) and the Standardized mortality ratio weighting (SMRW). Results of the example show that the distribution of the covariates tended to be consistent after weighting, and the IPTW and SMRW methods showed similar effect estimates. Propensity score weighting method can effectively balance the distribution of the confounding factors between the compared groups in non-randomized controlled trials.
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In this article, we presented the rationale and calculation procedures of a propensity score weighting method, with its application in epidemiological studies. The rationale for propensity score weighting method is similar to those for traditional standardization methods. Propensity score is used to estimate the weight for each individual. As the propensity score serves the function of observed covariates, the propensity score weighting can balance the distribution of the observed covariates between the comparison groups. There are two weighting methods according to the target standard populations: the Inverse probability of treatment weighting (IPTW) and the Standardized mortality ratio weighting (SMRW). Results of the example show that the distribution of the covariates tended to be consistent after weighting, and the IPTW and SMRW methods showed similar effect estimates. Propensity score weighting method can effectively balance the distribution of the confounding factors between the compared groups in non-randomized controlled trials.
Key concepts: Propensity score matching, Weighting, Covariate, Confounding, Statistics, Inverse probability weighting, A-weighting, Mathematics