方法证据记录
Inverse Probability Weighting
Inverse Probability Weighting is a causal-inference method that assigns each observation a weight equal to the inverse of its probability of receiving the treatment it actually received. Introduced by Robins, Hernán and Brumback (2000) for marginal structural models, it builds a pseudo-population in which treatment is independent of measured confounders, balancing selection bias.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Inverse Probability of Treatment Weighting (IPW / IPTW)
分类方法记录 · regression-model / causal-inference
- Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560. · DOI 10.1097/00001648-200009000-00011
- Cole, S. R., & Hernán, M. A. (2008). Constructing Inverse Probability Weights for Marginal Structural Models. American Journal of Epidemiology, 168(6), 656-664. · DOI 10.1093/aje/kwn164
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