Robust Estimation of Inverse Probability Weights for Marginal Structural Models

DOI10.1080/01621459.2014.956872zbMath1373.62158OpenAlexW2110153289MaRDI QIDQ5367415

Kosuke Imai, Marc Ratkovic

Publication date: 13 October 2017

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01621459.2014.956872

zbMATH Keywords

observational studiesrobust estimationcausal inferencemarginal structural modelscovariate balancing propensity scoresequential ignorabilityinverse propensity score weightingtime-dependent treatments

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric robustness (62G35) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to social sciences (62P25)

Related Items (11)

Heterogeneous indirect effects for multiple mediators using interventional effect models ⋮ Covariate balancing propensity score for a continuous treatment: application to the efficacy of political advertisements ⋮ Joint calibrated estimation of inverse probability of treatment and censoring weights for marginal structural models ⋮ Extending balance assessment for the generalized propensity score under multiple imputation ⋮ Treatment effects in interactive fixed effects models with a small number of time periods ⋮ Within-person variability score-based causal inference: a two-step estimation for joint effects of time-varying treatments ⋮ Bayesian Inference for Sequential Treatments Under Latent Sequential Ignorability ⋮ Empirical likelihood inference for partial functional linear model with missing responses ⋮ Covariate balancing functional propensity score for functional treatments in cross-sectional observational studies ⋮ Covariate-balancing-propensity-score-based inference for linear models with missing responses ⋮ Identification and sensitivity analysis for average causal mediation effects with time-varying treatments and mediators: investigating the underlying mechanisms of kindergarten retention policy

Uses Software

• CBPS

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