Matching methods for causal inference: a review and a look forward

DOI10.1214/09-STS313zbMath1328.62007arXiv1010.5586WikidataQ28749221 ScholiaQ28749221MaRDI QIDQ903298

Elizabeth A. Stuart

Publication date: 5 January 2016

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

Full work available at URL: https://arxiv.org/abs/1010.5586

zbMATH Keywords

weightingobservational studypropensity scoressubclassification

Mathematics Subject Classification ID

Design of statistical experiments (62K99) Research exposition (monographs, survey articles) pertaining to statistics (62-02)

Related Items (97)

The Landscape of Causal Inference: Perspective From Citation Network Analysis ⋮ The Central Role of Bayes’ Theorem for Joint Estimation of Causal Effects and Propensity Scores ⋮ Ridge rerandomization: an experimental design strategy in the presence of covariate collinearity ⋮ Kernel canonical correlation analysis for data combination of multiple-source datasets ⋮ Covariate matching methods for testing and quantifying wind turbine upgrades ⋮ Full matching approach to instrumental variables estimation with application to the effect of malaria on stunting ⋮ The Case-Control Approach Can be More Powerful for Matched Pair Observational Studies When the Outcome is Rare ⋮ Generalized Optimal Matching Methods for Causal Inference ⋮ Improving Effect Estimates by Limiting the Variability in Inverse Propensity Score Weights ⋮ Being a public health statistician during a global pandemic ⋮ The role of statistics in the era of big data: electronic health records for healthcare research ⋮ Sufficient dimension reduction for average causal effect estimation ⋮ A Computational Framework for Solving Nonlinear Binary Optimization Problems in Robust Causal Inference ⋮ Optimal Matching with Minimal Deviation from Fine Balance in a Study of Obesity and Surgical Outcomes ⋮ 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 ⋮ Building Representative Matched Samples With Multi-Valued Treatments in Large Observational Studies ⋮ Detecting heterogeneous treatment effects with instrumental variables and application to the Oregon Health Insurance Experiment ⋮ Outcome-adjusted balance measure for generalized propensity score model selection ⋮ Sharpening the Rosenbaum Sensitivity Bounds to Address Concerns About Interactions Between Observed and Unobserved Covariates ⋮ On point estimation of the abnormality of a Mahalanobis index ⋮ Maximum entropy in the mean methods in propensity score matching for interval and noisy data ⋮ The causal effect of a timeout at stopping an opposing run in the NBA ⋮ Estimating causal effects with optimization-based methods: a review and empirical comparison ⋮ On the support of matching algorithms ⋮ Some models and methods for the analysis of observational data ⋮ Evaluation of the health impacts of the 1990 Clean Air Act Amendments using causal inference and machine learning ⋮ Evaluating and improving a matched comparison of antidepressants and bone density ⋮ Causal inference: Critical developments, past and future ⋮ Better experimental design by hybridizing binary matching with imbalance optimization ⋮ Causal inference for multiple treatments using fractional factorial designs ⋮ Equal percent bias reduction and variance proportionate modifying properties with mean-covariance preserving matching ⋮ Estimating propensity scores using neural networks and traditional methods: a comparative simulation study ⋮ Evaluating different groups of mutual funds using a metafrontier approach: ethical vs. non-ethical funds ⋮ A Review of Spatial Causal Inference Methods for Environmental and Epidemiological Applications ⋮ Testing Weak Nulls in Matched Observational Studies ⋮ How Well Can Fine Balance Work for Covariate Balancing ⋮ Multiple imputation regression discontinuity designs: Alternative to regression discontinuity designs to estimate the local average treatment effect at the cutoff ⋮ Testing Biased Randomization Assumptions and Quantifying Imperfect Matching and Residual Confounding in Matched Observational Studies ⋮ Assignment-Control Plots: A Visual Companion for Causal Inference Study Design ⋮ Rather “Good In, Good Out” Than “Garbage In, Garbage Out”: A Comparison of Various Discrete Subsampling Algorithms Using COVID-19 Data Without a Response Variable ⋮ Constrained optimization for stratified treatment rules in reducing hospital readmission rates of diabetic patients ⋮ Bayesian causal inference with bipartite record linkage ⋮ Selecting intervals to optimize the design of observational studies subject to fine balance constraints ⋮ Causal inference in data analysis with applications to fairness and explanations ⋮ Using predictability to improve matching of urban locations in Philadelphia ⋮ A latent class model to multiply impute missing treatment indicators in observational studies when inferences of the treatment effect are made using propensity score matching ⋮ Prior-Preconditioned Conjugate Gradient Method for Accelerated Gibbs Sampling in “Large n , Large p ” Bayesian Sparse Regression ⋮ Addressing substantial covariate imbalance with propensity score stratification and balancing weights: connections and recommendations ⋮ Social distancing and COVID-19: randomization inference for a structured dose-response relationship ⋮ Bayesian approach for addressing differential covariate measurement error in propensity score methods ⋮ Statistical matching and subclassification with a continuous dose: characterization, algorithm, and application to a health outcomes study ⋮ Leveraging population outcomes to improve the generalization of experimental results: application to the JTPA study ⋮ Bayesian Nonparametric Common Atoms Regression for Generating Synthetic Controls in Clinical Trials ⋮ Combining Multiple Observational Data Sources to Estimate Causal Effects ⋮ Stronger instruments via integer programming in an observational study of late preterm birth outcomes ⋮ Matching methods for observational studies derived from large administrative databases ⋮ Commentary on Yu et al..: Opportunities and challenges for matching methods in large databases ⋮ Double robustness without weighting ⋮ Split-door criterion: identification of causal effects through auxiliary outcomes ⋮ Matching for balance, pairing for heterogeneity in an observational study of the effectiveness of for-profit and not-for-profit high schools in Chile ⋮ Covariate balancing propensity score by tailored loss functions ⋮ On Propensity Score Methodology ⋮ A multiple imputation procedure for record linkage and causal inference to estimate the effects of home-delivered meals ⋮ Matched Learning for Optimizing Individualized Treatment Strategies Using Electronic Health Records ⋮ Using Mixed Integer Programming for Matching in an Observational Study of Kidney Failure After Surgery ⋮ Covariate balancing functional propensity score for functional treatments in cross-sectional observational studies ⋮ Contrasting Evidence Within and Between Institutions That Provide Treatment in an Observational Study of Alternate Forms of Anesthesia ⋮ Rejoinder: Bayesian Effect Estimation Accounting for Adjustment Uncertainty ⋮ Estimation of causal effects with multiple treatments: a review and new ideas ⋮ All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously ⋮ Nonparametric Bayesian Multiple Imputation for Missing Data Due to Mid-Study Switching of Measurement Methods ⋮ Bayesian method for causal inference in spatially-correlated multivariate time series ⋮ Impact of Multiple Matched Controls on Design Sensitivity in Observational Studies ⋮ Model Feedback in Bayesian Propensity Score Estimation ⋮ Isolation in the construction of natural experiments ⋮ Learning causal effect using machine learning with application to China's typhoon ⋮ Measuring model misspecification: application to propensity score methods with complex survey data ⋮ Using Approximation Algorithms to Build Evidence Factors and Related Designs for Observational Studies ⋮ Causal inference: a missing data perspective ⋮ Robust Alternatives to ANCOVA for Estimating the Treatment Effect via a Randomized Comparative Study ⋮ Assessing the causal effect of binary interventions from observational panel data with few treated units ⋮ Kernel Balancing: A flexible non-parametric weighting procedure for estimating causal effects ⋮ Is Early Smoking a Causal Risk Factor for Later Cognitive Impairment? A 20-year Prospective Study with Time-varying Propensity Score Matching Based on Random Intercept and Slope ⋮ Clustered Treatment Assignments and Sensitivity to Unmeasured Biases in Observational Studies ⋮ Weighted M-statistics With Superior Design Sensitivity in Matched Observational Studies With Multiple Controls ⋮ Correlation and efficiency of propensity score-based estimators for average causal effects ⋮ The designed bootstrap for causal inference in big observational data ⋮ Extended sensitivity analysis for heterogeneous unmeasured confounding with an application to sibling studies of returns to education ⋮ Advancing statistical thinking in observational health care research ⋮ The statistical performance of matching-adjusted indirect comparisons: estimating treatment effects with aggregate external control data ⋮ Automated versus do-it-yourself methods for causal inference: lessons learned from a data analysis competition ⋮ Optimal Tradeoffs in Matched Designs Comparing US-Trained and Internationally Trained Surgeons ⋮ Discovering Heterogeneous Exposure Effects Using Randomization Inference in Air Pollution Studies ⋮ Accounting for matching structure in post-matching analysis of observational studies ⋮ Using the Exterior Match to Compare Two Entwined Matched Control Groups ⋮ Network flow methods for the minimum covariate imbalance problem

Uses Software

• twang
• cem
• rbounds
• DOS

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Doubly Robust Estimation in Missing Data and Causal Inference Models
• The prognostic analogue of the propensity score
• Demystifying double robustness: a comparison of alternative strategies for estimating a population mean from incomplete data
• Affinely invariant matching methods with discriminant mixtures of proportional ellipsoidally symmetric distributions
• The foundations of confounding in epidemiology
• Affinely invariant matching methods with ellipsoidal distributions
• Confounding and collapsibility in causal inference
• Choice as an alternative to control in observational studies. (With comments and a rejoinder).
• Using Multivariate Matched Sampling and Regression Adjustment to Control Bias in Observational Studies
• Principal Stratification in Causal Inference
• Using the Standardized Difference to Compare the Prevalence of a Binary Variable Between Two Groups in Observational Research
• Matched Sampling for Causal Effects
• What Do Randomized Studies of Housing Mobility Demonstrate?
• Dealing with limited overlap in estimation of average treatment effects
• Toward Causal Inference With Interference
• The central role of the propensity score in observational studies for causal effects
• Statistics and Causal Inference
• The Bias Due to Incomplete Matching
• Model-Based Direct Adjustment
• Matching As An Econometric Evaluation Estimator
• Bias Reduction Using Mahalanobis-Metric Matching
• Characterizing the effect of matching using linear propensity score methods with normal distributions
• Multivariate Matching Methods That are Equal Percent Bias Reducing, I: Some Examples
• Inference and missing data
• Matching when covariables are normally distributed
• Matching Using Estimated Propensity Scores: Relating Theory to Practice
• Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme
• Balanced Risk Set Matching
• Matching With Doses in an Observational Study of a Media Campaign Against Drug Abuse
• The role of the propensity score in estimating dose-response functions
• Characterizing Selection Bias Using Experimental Data
• Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models
• Estimating Exposure Effects by Modelling the Expectation of Exposure Conditional on Confounders
• Some Practical Issues in the Evaluation of Heterogeneous Labour Market Programmes by Matching Methods
• Semiparametric Efficiency in Multivariate Regression Models with Missing Data
• Split Samples and Design Sensitivity in Observational Studies
• Minimum Distance Matched Sampling With Fine Balance in an Observational Study of Treatment for Ovarian Cancer
• Bias-Corrected Matching Estimators for Average Treatment Effects
• Large Sample Properties of Matching Estimators for Average Treatment Effects
• Can Nonrandomized Experiments Yield Accurate Answers? A Randomized Experiment Comparing Random and Nonrandom Assignments
• Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score
• Optimal multivariate matching before randomization
• Full Matching in an Observational Study of Coaching for the SAT
• Causal Inference With General Treatment Regimes
• Evaluating Kindergarten Retention Policy
• A Generalization of Sampling Without Replacement From a Finite Universe
• Design of observational studies
• Observational studies.

This page was built for publication: Matching methods for causal inference: a review and a look forward