Inverse probability weighting for causal inference in hierarchical data [PDF]
Objective The aim of this study was to explore the impact of model misspecification, balance, and extreme weights on average treatment effect (ATE) estimation in hierarchical data with unmeasured cluster-level confounders using the multilevel propensity ...
Lin Hu +10 more
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Normalized Augmented Inverse Probability Weighting with Neural Network Predictions [PDF]
The estimation of average treatment effect (ATE) as a causal parameter is carried out in two steps, where in the first step, the treatment and outcome are modeled to incorporate the potential confounders, and in the second step, the predictions are ...
Mehdi Rostami, Olli Saarela
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Inverse Probability Weighting Enhances Absolute Risk Estimation in Three Common Study Designs of Nosocomial Infections [PDF]
Paulina Staus,1 Maja von Cube,1,* Derek Hazard,1,* Sam Doerken,1 Ksenia Ershova,2 James Balmford1 ,† Martin Wolkewitz1 1Institute of Medical Biometry and Statistics, Division Methods in Clinical Epidemiology, Faculty of Medicine and Medical ...
Staus P +6 more
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Correlation between metabolic unhealth and prostate cancer -an inverse probability weighting study [PDF]
Background Current research indicates that prostate cancer (PCa) is one of the most common cancers in men, and its occurrence may be linked to metabolic unhealth.
Mingyue Chen +5 more
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Augmented Inverse Probability Weighting and the Double Robustness Property [PDF]
This article discusses the augmented inverse propensity weighted (AIPW) estimator as an estimator for average treatment effects. The AIPW combines both the properties of the regression-based estimator and the inverse probability weighted (IPW) estimator and is therefore a “doubly robust” method in that it requires only either the propensity or outcome ...
Kurz CF.
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Deep sedation for nasal septal surgery: an observational retrospective study with an inverse probability weighting model [PDF]
Background Septoplasty, a common surgical procedure to correct a deviated septum, can be performed under either general anesthesia or deep sedation anesthesia.
Laura Campiglia +5 more
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Stabilized Inverse Probability Weighting via Isotonic Calibration [PDF]
Accepted to CLeaR conference (2025). Companion paper: Automatic doubly robust inference for linear functionals via calibrated debiased machine learning, arXiv:2411 ...
Lars van der Laan +3 more
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On Variance of the Treatment Effect in the Treated When Estimated by Inverse Probability Weighting [PDF]
Sarah A Reifeis +2 more
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Non-Asymptotic Bounds of AIPW Estimators for Means with Missingness at Random
The augmented inverse probability weighting is well known for its double robustness in missing data and causal inference. If either the propensity score model or the outcome regression model is correctly specified, the estimator is guaranteed to be ...
Fei Wang, Yuhao Deng
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In this Monte Carlo simulation study, the performance of six different propensity score methods implemented through weighting cases was investigated: inverse probability of treatment weighting, truncated inverse probability of treatment weighting ...
Sungur Gürel, Walter Lana Leite
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