Causal Inference With General Treatment Regimes

From MaRDI portal
Publication:5754784

DOI10.1198/016214504000001187zbMath1117.62361OpenAlexW2111078766MaRDI QIDQ5754784

Kosuke Imai, David A. van Dyk

Publication date: 20 August 2007

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

Full work available at URL: https://doi.org/10.1198/016214504000001187



Related Items

Nonparametric Tests of the Causal Null With Nondiscrete Exposures, Entropy balancing for continuous treatments, The Landscape of Causal Inference: Perspective From Citation Network Analysis, Efficient semiparametric estimation of multi-valued treatment effects under ignorability, Estimating the causal effects of marketing interventions using propensity score methodology, 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, Balancing Covariates via Propensity Score Weighting, Covariates distributions balancing for continuous treatment, Double robust estimator in general treatment regimes based on Covariate-balancing, Multiple comparisons for survival data with propensity score adjustment, ROC analysis using covariate balancing propensity scores with an application to biochemical predictors for thyroid cancer, Multiple mediation analysis for interval-valued data, 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, Estimating the optimal timing of surgery from observational data, Change-Plane Analysis for Subgroup Detection with a Continuous Treatment, Generalized Propensity Score Approach to Causal Inference with Spatial Interference, Variance estimators for weighted and stratified linear dose–response function estimators using generalized propensity score, A new covariate selection strategy for high dimensional data in causal effect estimation with multivariate treatments, Causal inference under mis-specification: adjustment based on the propensity score (with discussion), A causal exposure response function with local adjustment for confounding: estimating health effects of exposure to low levels of ambient fine particulate matter, 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, Estimating Density Ratio of Marginals to Joint: Applications to Causal Inference, Balancing scores for simultaneous comparisons of multiple treatments, Extending balance assessment for the generalized propensity score under multiple imputation, Matching methods for causal inference: a review and a look forward, Matching on Generalized Propensity Scores with Continuous Exposures, Flexible Sensitivity Analysis for Observational Studies Without Observable Implications, Robust inference on average treatment effects with possibly more covariates than observations, Covariate balancing functional propensity score for functional treatments in cross-sectional observational studies, Rejoinder: Bayesian Effect Estimation Accounting for Adjustment Uncertainty, Estimation of causal effects with multiple treatments: a review and new ideas, Efficient propensity score regression estimators of multivalued treatment effects for the treated, Dimension reduction summaries for balanced contrasts, Joint sufficient dimension reduction for estimating continuous treatment effect functions, Measuring model misspecification: application to propensity score methods with complex survey data, Accounting for uncertainty in confounder and effect modifier selection when estimating average causal effects in generalized linear models, Using Approximation Algorithms to Build Evidence Factors and Related Designs for Observational Studies, The Blessings of Multiple Causes, Causal inference: a missing data perspective, Bayesian regression tree models for causal inference: regularization, confounding, and heterogeneous effects (with discussion), Continuous treatment effect estimation via generative adversarial de-confounding, A Causal Model for Joint Evaluation of Placebo and Treatment‐Specific Effects in Clinical Trials, Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level, Modeling temporal treatment effects with zero inflated semi-parametric regression models: The case of local development policies in France, On the power of conditional independence testing under model-X, Assessing the effect of the amount of financial aids to Piedmont firms using the generalized propensity score, Estimation and inference for the counterfactual distribution and quantile functions in continuous treatment models, Landmark estimation of survival and treatment effects in observational studies