Every reference with a DOI in the deposited reference list resolved to a known
work in Crossref or DataCite at the dated check, and none carried a retraction,
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The 67 checked references that resolve
resolves10.1037/1082-989X.9.4.403Propensity Score Estimation With Boosted Regression for Evaluating Causal Effects in Observational Studies.
resolves10.1111/biom.13405Power and sample size for observational studies of point exposure effects
resolves10.1080/00273171.2011.568786An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies
resolves10.3102/1076998609359785Marginal Mean Weighting Through Stratification: Adjustment for Selection Bias in Multilevel Data
resolves10.1097/EDE.0000000000000595A Propensity-score-based Fine Stratification Approach for Confounding Adjustment When Exposure Is Infrequent
resolves10.1214/19-AOAS1282Propensity score weighting for causal inference with multiple treatments
resolves10.1002/sim.5753A tutorial on propensity score estimation for multiple treatments using generalized boosted models
resolves10.1037/a0024918Marginal mean weighting through stratification: A generalized method for evaluating multivalued and multiple treatments with nonexperimental data.
resolves10.1214/17-AOAS1101Covariate balancing propensity score for a continuous treatment: Application to the efficacy of political advertisements
resolves10.1515/jci-2017-0002Covariate Balancing Inverse Probability Weights for Time-Varying Continuous Interventions
resolves10.48550/arXiv.2601.15449Distributional Balancing for Causal Inference: A Unified Framework via Characteristic Function Distance
resolves10.1093/pan/mpr025Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies
resolves10.1007/s10742-020-00236-2Nonparametric estimation of population average dose-response curves using entropy balancing weights for continuous exposures
resolves10.1515/jci-2014-0022A Boosting Algorithm for Estimating Generalized Propensity Scores with Continuous Treatments
resolves10.1002/sim.7273Firth's logistic regression with rare events: accurate effect estimates and predictions?
resolves10.1016/j.csda.2019.106907Logistic regression with missing covariates—Parameter estimation, model selection and prediction within a joint-modeling framework
resolves10.1093/biomet/asz050Minimal dispersion approximately balancing weights: asymptotic properties and practical considerations
resolves10.1111/rssa.12561Direct and Stable Weight Adjustment in Non-Experimental Studies With Multivalued Treatments: Analysis of the Effect of an Earthquake on Post-Traumatic Stress
resolves10.17615/DYSS-B342Estimating Balancing Weights for Continuous Treatments Using Constrained Optimization
resolves10.1093/aje/kwu253Improving Propensity Score Estimators' Robustness to Model Misspecification Using Super Learner
resolves10.1002/hec.3189Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury
resolves10.1177/0962280216682055The Balance Super Learner: A robust adaptation of the
<i>Super Learner</i>
to improve estimation of the average treatment effect in the treated based on propensity score matching
resolves10.1093/aje/kwn164Constructing Inverse Probability Weights for Marginal Structural Models
resolves10.1002/sim.7084Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis
resolves10.1002/sim.9519Bootstrap vs asymptotic variance estimation when using propensity score weighting with continuous and binary outcomes
resolves10.1111/rssb.12129Globally Efficient Non-Parametric Inference of Average Treatment Effects by Empirical Balancing Calibration Weighting
resolves10.1002/sim.9969Inverse probability of treatment weighting with generalized linear outcome models for doubly robust estimation
resolves10.1002/bimj.201700330Closed‐form variance estimator for weighted propensity score estimators with survival outcome
resolves10.1093/pan/mpl013Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference
resolves10.1002/sim.1903Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study
resolves10.1002/sim.7839On the propensity score weighting analysis with survival outcome: Estimands, estimation, and inference
resolves10.1186/s12874-017-0338-0Double-adjustment in propensity score matching analysis: choosing a threshold for considering residual imbalance
resolves10.1093/aje/kwac014On Variance of the Treatment Effect in the Treated When Estimated by Inverse Probability Weighting
resolves10.1093/ije/dyae030M-estimation for common epidemiological measures: introduction and applied examples
resolves10.1037/a0014268Average causal effects from nonrandomized studies: A practical guide and simulated example.
resolves10.1093/aje/kwq472Implementation of G-Computation on a Simulated Data Set: Demonstration of a Causal Inference Technique
resolves10.1093/aje/kws412The Table 2 Fallacy: Presenting and Interpreting Confounder and Modifier Coefficients
resolves10.1002/sim.6607Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies
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