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Residual Balancing: A Method of Constructing Weights for Marginal Structural Models
[article]
2019
arXiv
pre-print
When making causal inferences, post-treatment confounders complicate analyses of time-varying treatment effects. Conditioning on these variables naively to estimate marginal effects may inappropriately block causal pathways and may induce spurious associations between treatment and the outcome, leading to bias. To avoid such bias, researchers often use marginal structural models (MSMs) with inverse probability weighting (IPW). However, IPW requires models for the conditional distributions of
arXiv:1807.10869v2
fatcat:m47qkhu63fa7behcksbexfkgy4