Estimation with missing data: beyond double robustness
From MaRDI portal
Publication:5411043
DOI10.1093/biomet/ass087zbMath1284.62260OpenAlexW2127699081MaRDI QIDQ5411043
Publication date: 22 April 2014
Published in: Biometrika (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1093/biomet/ass087
missing at randomempirical likelihoodsemiparametric efficiencycausal inferenceaugmented inverse probability weighting
Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Nonparametric robustness (62G35) Nonparametric estimation (62G05)
Related Items (42)
Causal inference with missingness in confounder ⋮ Model averaged double robust estimation ⋮ A beyond multiple robust approach for missing response problem ⋮ Optimal treatment regimes for competing risk data using doubly robust outcome weighted learning with bi-level variable selection ⋮ Ensemble and calibration multiply robust estimation for quantile treatment effect ⋮ Robust Bayesian inference for big data: combining sensor-based records with traditional survey data ⋮ A fusion of least squares and empirical likelihood for regression models with a missing binary covariate ⋮ Estimation of the average causal effect via multiple propensity score stratification ⋮ Empirical likelihood method for non-ignorable missing data problems ⋮ Multiple robustness estimation in causal inference ⋮ Jackknife empirical likelihood method for multiply robust estimation with missing data ⋮ Multiply Robust Estimation in Regression Analysis With Missing Data ⋮ Robust estimation of models for longitudinal data with dropouts and outliers ⋮ Doubly robust estimator for net survival rate in analyses of cancer registry data ⋮ General purpose multiply robust data integration procedures for handling nonprobability samples ⋮ Robust quasi‐randomization‐based estimation with ensemble learning for missing data ⋮ Nested doubly robust estimating equations for causal analysis with an incomplete effect modifier ⋮ Integrating information from existing risk prediction models with no model details ⋮ Calibrated regression estimation using empirical likelihood under data fusion ⋮ Multiply robust estimation of the average treatment effect with missing outcomes ⋮ A multiple robust propensity score method for longitudinal analysis with intermittent missing data ⋮ Noniterative adjustment to regression estimators with population‐based auxiliary information for semiparametric models ⋮ Multiply robust imputation procedures for zero-inflated distributions in surveys ⋮ Calibration Techniques Encompassing Survey Sampling, Missing Data Analysis and Causal Inference ⋮ Recent Developments in Dealing with Item Non‐response in Surveys: A Critical Review ⋮ A semiparametric multiply robust multiple imputation method for causal inference ⋮ Handling high-dimensional data with missing values by modern machine learning techniques ⋮ A unified framework of multiply robust estimation approaches for handling incomplete data ⋮ A multiply robust Mann-Whitney test for non-randomised pretest-posttest studies with missing data ⋮ A further study of the multiply robust estimator in missing data analysis ⋮ A unified empirical likelihood approach for testing MCAR and subsequent estimation ⋮ Empirical likelihood inference for non-randomized pretest-posttest studies with missing data ⋮ Stratified doubly robust estimators for the average causal effect ⋮ Achieving semiparametric efficiency bound in longitudinal data analysis with dropouts ⋮ Calibration estimation of semiparametric copula models with data missing at random ⋮ Combining Inverse Probability Weighting and Multiple Imputation to Improve Robustness of Estimation ⋮ Robust estimation for moment condition models with data missing not at random ⋮ Multiply robust estimation in nonparametric regression with missing data ⋮ Penalized multiply robust estimation in high-order autoregressive processes with missing explanatory variables ⋮ Semiparametric estimation in regression with missing covariates using single-index models ⋮ Comments on: ``Deville and Särndal's calibration: revisiting a 25 years old successful optimization problem ⋮ Oracle, multiple robust and multipurpose calibration in a missing response problem
This page was built for publication: Estimation with missing data: beyond double robustness