Demystifying double robustness: a comparison of alternative strategies for estimating a population mean from incomplete data

DOI10.1214/07-STS227zbMath1246.62073arXiv0804.2958OpenAlexW3122781290WikidataQ31157218 ScholiaQ31157218MaRDI QIDQ449788

Joseph L. Schafer, Joseph D. Y. Kang

Publication date: 1 September 2012

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0804.2958

zbMATH Keywords

missing data causal inference propensity score model-assisted survey estimation weighted estimating equations

Mathematics Subject Classification ID

Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).

Related Items (only showing first 100 items - show all)

Causal inference with missingness in confounder ⋮ Impact of sufficient dimension reduction in nonparametric estimation of causal effect ⋮ On valid descriptive inference from non-probability sample ⋮ Discussions ⋮ Discussions ⋮ Semiparametric Inference of Causal Effect with Nonignorable Missing Confounders ⋮ Matrix Completion under Low-Rank Missing Mechanism ⋮ Ensemble and calibration multiply robust estimation for quantile treatment effect ⋮ Visually Communicating and Teaching Intuition for Influence Functions ⋮ Improving Effect Estimates by Limiting the Variability in Inverse Propensity Score Weights ⋮ A comparative study of doubly robust estimators of the mean with missing data ⋮ A Simple and Efficient Estimation of Average Treatment Effects in Models with Unmeasured Confounders ⋮ A stable and more efficient doubly robust estimator ⋮ On Semiparametric Instrumental Variable Estimation of Average Treatment Effects through Data Fusion ⋮ Double robust estimator in general treatment regimes based on Covariate-balancing ⋮ Comparing different propensity score estimation methods for estimating the marginal causal effect through standardization to propensity scores ⋮ Confounding adjustment methods for multi-level treatment comparisons under lack of positivity and unknown model specification ⋮ Estimation and Validation of Ratio-based Conditional Average Treatment Effects Using Observational Data ⋮ Doubly robust estimator for net survival rate in analyses of cancer registry data ⋮ Estimating a causal exposure response function with a continuous error-prone exposure: a study of fine particulate matter and all-cause mortality ⋮ General purpose multiply robust data integration procedures for handling nonprobability samples ⋮ Robust quasi‐randomization‐based estimation with ensemble learning for missing data ⋮ Comparison of covariate balance weighting methods in estimating treatment effects ⋮ Joint calibrated estimation of inverse probability of treatment and censoring weights for marginal structural models ⋮ Nonparametric Inverse-Probability-Weighted Estimators Based on the Highly Adaptive Lasso ⋮ Causal inference: Critical developments, past and future ⋮ Coarsened Propensity Scores and Hybrid Estimators for Missing Data and Causal Inference ⋮ Estimation for volunteer web survey samples using a model-averaging approach ⋮ Subclassification estimation of the weighted average treatment effect ⋮ Discussion on “Correct and logical causal inference for binary and time‐to‐event outcomes in randomized controlled trials” by Yi Liu, Bushi Wang, Miao Yang, Jianan Hui, Heng Xu, Siyoen Kil, and Jason C. Hsu ⋮ Causal inference in case of near‐violation of positivity: comparison of methods ⋮ A semiparametric method for evaluating causal effects in the presence of error‐prone covariates ⋮ Instrumental Variable Estimation of the Causal Hazard Ratio ⋮ Calibration Techniques Encompassing Survey Sampling, Missing Data Analysis and Causal Inference ⋮ Semiparametric estimation of long-term treatment effects ⋮ Nonparametric regression with nonignorable missing covariates and outcomes using bounded inverse weighting ⋮ Semiparametric Bayesian doubly robust causal estimation ⋮ A semiparametric multiply robust multiple imputation method for causal inference ⋮ The Generalized Oaxaca-Blinder Estimator ⋮ Handling high-dimensional data with missing values by modern machine learning techniques ⋮ Identification, Semiparametric Efficiency, and Quadruply Robust Estimation in Mediation Analysis with Treatment-Induced Confounding ⋮ A unified framework of multiply robust estimation approaches for handling incomplete data ⋮ Leveraging population outcomes to improve the generalization of experimental results: application to the JTPA study ⋮ Projected state-action balancing weights for offline reinforcement learning ⋮ RKHS-based covariate balancing for survival causal effect estimation ⋮ Matching on Generalized Propensity Scores with Continuous Exposures ⋮ Doubly Robust Inference With Nonprobability Survey Samples ⋮ CBPS-based estimation for linear models with responses missing at random ⋮ Unnamed Item ⋮ Unnamed Item ⋮ Stratified doubly robust estimators for the average causal effect ⋮ Test the reliability of doubly robust estimation with missing response data ⋮ Rejoinder ⋮ Multiply robust estimation in nonparametric regression with missing data ⋮ A comparison of doubly robust estimators of the mean with missing data ⋮ Penalized Spline of Propensity Methods for Treatment Comparison ⋮ Discussion of PENCOMP ⋮ Comment: Penalized Spline of Propensity Methods for Treatment Comparison ⋮ Nonparametric Causal Effects Based on Incremental Propensity Score Interventions ⋮ PROPERTIES OF DOUBLY ROBUST ESTIMATORS WHEN NUISANCE FUNCTIONS ARE ESTIMATED NONPARAMETRICALLY ⋮ Improved Doubly Robust Estimation in Learning Optimal Individualized Treatment Rules ⋮ Robust Q-Learning ⋮ Empirical Likelihood in Causal Inference ⋮ Accounting for matching structure in post-matching analysis of observational studies ⋮ Comparing the performance of statistical methods that generalize effect estimates from randomized controlled trials to much larger target populations ⋮ On model selection and model misspecification in causal inference ⋮ Propensity score prediction for electronic healthcare databases using super learner and high-dimensional propensity score methods ⋮ Bayesian semiparametric modeling of response mechanism for nonignorable missing data ⋮ Determination of the optimal number of strata for propensity score subclassification ⋮ Using missing types to improve partial identification with application to a study of HIV prevalence in Malawi ⋮ Robust inference using hierarchical likelihood approach for heavy-tailed longitudinal outcomes with missing data: an alternative to inverse probability weighted generalized estimating equations ⋮ Adjustments and their Consequences-Collapsibility Analysis using Graphical Models ⋮ Statistical data integration in survey sampling: a review ⋮ Semiparametric estimation for average causal effects using propensity score-based spline ⋮ Doubly robust semiparametric inference using regularized calibrated estimation with high-dimensional data ⋮ Effects of correlated covariates on the asymptotic efficiency of matching and inverse probability weighting estimators for causal inference ⋮ Covariate balancing propensity score for a continuous treatment: application to the efficacy of political advertisements ⋮ Robust Bayesian inference for big data: combining sensor-based records with traditional survey data ⋮ Augmented direct learning for conditional average treatment effect estimation with double robustness ⋮ Optimal Probability Weights for Inference With Constrained Precision ⋮ Model averaging procedure for varying-coefficient partially linear models with missing responses ⋮ The finite sample performance of semi- and non-parametric estimators for treatment effects and policy evaluation ⋮ Estimation of the average causal effect via multiple propensity score stratification ⋮ Simultaneous mean and covariance estimation of partially linear models for longitudinal data with missing responses and covariate measurement error ⋮ Jackknife empirical likelihood method for multiply robust estimation with missing data ⋮ Estimation of partially conditional average treatment effect by double kernel-covariate balancing ⋮ Multiply Robust Estimation in Regression Analysis With Missing Data ⋮ Efficient estimation of quantiles in missing data models ⋮ Estimating multiple treatment effects using two-phase semiparametric regression estimators ⋮ Effect of breastfeeding on gastrointestinal infection in infants: a targeted maximum likelihood approach for clustered longitudinal data ⋮ Overlap weight and propensity score residual for heterogeneous effects: a review with extensions ⋮ A Mann-Whitney test of distributional effects in a multivalued treatment ⋮ Multiply robust imputation procedures for zero-inflated distributions in surveys ⋮ Second-order asymptotic theory for calibration estimators in sampling and missing-data problems ⋮ Causal mediation analysis: from simple to more robust strategies for estimation of marginal natural (in)direct effects ⋮ Estimation and inference in metabolomics with nonrandom missing data and latent factors ⋮ Double-estimation-friendly inference for high-dimensional misspecified models ⋮ A GENERAL DOUBLE ROBUSTNESS RESULT FOR ESTIMATING AVERAGE TREATMENT EFFECTS ⋮ Large dimensional latent factor modeling with missing observations and applications to causal inference ⋮ Matching methods for causal inference: a review and a look forward

Uses Software

BayesDA

Cites Work

This page was built for publication: Demystifying double robustness: a comparison of alternative strategies for estimating a population mean from incomplete data