Cover Image

Moving toward best practice when using propensity score weighting in survey observational studies

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zeng, Yukang, Li, Fan, Tong, Guangyu
Format:	Preprint
Published:	2025
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Robust propensity score weighting estimation under missing at random
by: Wang, Hengfang, et al.
Published: (2023)

Testing for causal effect for binary data when propensity scores are estimated through Bayesian Networks
by: Vicard, Paola, et al.
Published: (2023)

Propensity score weighted Cox regression for survival outcomes in observational studies with multiple or factorial treatments
by: Zhao, Zixian, et al.
Published: (2026)

Adjusted Nelson--Aalen estimators by inverse treatment probability weighting with an estimated propensity score
by: Deng, Yuhao, et al.
Published: (2024)

A tutorial for propensity score weighting methods under violations of the positivity assumption
by: Liu, Yi, et al.
Published: (2025)

Isotonic propensity score matching
by: Xu, Mengshan, et al.
Published: (2022)

Improving operating characteristics of clinical trials by augmenting control arm using propensity score-weighted borrowing-by-parts power prior
by: Das, Apu Chandra, et al.
Published: (2026)

Adjusting for indirectly measured confounding using large-scale propensity scores
by: Zhang, Linying, et al.
Published: (2021)

Exact matching as an alternative to propensity score matching
by: Glimm, Ekkehard, et al.
Published: (2025)

High confidence inference on the probability an individual benefits from treatment using experimental or observational data with known propensity scores
by: Ruiz, Gabriel, et al.
Published: (2022)

A subgroup-aware scoring approach to the study of effect modification in observational studies
by: Fan, Yijun, et al.
Published: (2024)

Moving Toward Best Practice When Using Propensity Score Weighting in Survey Observational Studies
by: Yukang Zeng, et al.
Published: (2026)

Evaluating the impact of instrumental variables in propensity score models using synthetic and negative control experiments
by: Tian, Yuxi, et al.
Published: (2024)

Interpolated stochastic interventions based on propensity scores, target policies and treatment-specific costs
by: de Aguas, Johan
Published: (2025)

Extension of Dynamic Network Biomarker using the propensity score method: Simulation of causal effects on variance and correlation coefficient
by: Shinoda, Satoru, et al.
Published: (2025)

A comparative study of augmented inverse propensity weighted estimators using outcome-oriented covariate selection via penalization with outcome-adaptive lasso
by: Hongo, Wataru, et al.
Published: (2024)

A goodness-of-fit test for the logistic propensity score model under nonignorable missing data
by: Cheng, Manli, et al.
Published: (2026)

Doubly robust estimation and sensitivity analysis with outcomes truncated by death in multi-arm clinical trials
by: Tong, Jiaqi, et al.
Published: (2024)

Principal stratification with recurrent events truncated by a terminal event: A nested Bayesian nonparametric approach
by: Ohnishi, Yuki, et al.
Published: (2025)

Propensity score models are better when post-calibrated
by: Gutman, Rom, et al.
Published: (2022)

Propensity score adjustment when errors in achievement measures inform treatment assignment
by: Wasserman, Joshua, et al.
Published: (2025)

Can discrete-time analyses be trusted for stepped wedge trials with continuous recruitment?
by: Wang, Hao, et al.
Published: (2025)

Bayesian inference for cluster-randomized trials with multivariate outcomes subject to both truncation by death and missingness
by: Tong, Guangyu, et al.
Published: (2025)

Neyman-Pearson and equal opportunity: when efficiency meets fairness in classification
by: Fan, Jianqing, et al.
Published: (2023)

Uncovering Treatment Effect Heterogeneity in Pragmatic Gerontology Trials
by: Li, Changjun, et al.
Published: (2025)

Doubly robust estimators of the restricted mean time in favor estimands in individual- and cluster-randomized trials
by: Fang, Xi, et al.
Published: (2026)

Sensitivity analysis for causal mediation: bridge score, sharp sensitivity bounds, and calibration
by: Ohnishi, Yuki, et al.
Published: (2026)

Lord's 'paradox' explained: the 50-year warning on the use of 'change scores' in observational data
by: Tennant, Peter W. G., et al.
Published: (2023)

Propensity score weighting across counterfactual worlds: longitudinal effects under positivity violations
by: McClean, Alec, et al.
Published: (2025)

Statistical inference with win statistics in cluster-randomized trials with composite outcomes
by: Fang, Xi, et al.
Published: (2026)

Addressing selection bias in cluster randomized experiments via weighting
by: Papadogeorgou, Georgia, et al.
Published: (2023)

Covariate-adjusted win statistics in randomized clinical trials with ordinal outcomes
by: Cao, Zhiqiang, et al.
Published: (2025)

Sample size and power calculations for causal inference of observational studies
by: Liu, Bo, et al.
Published: (2025)

Leveraging machine learning to estimate individualized treatment effects in cluster-randomized trials
by: Li, Changjun, et al.
Published: (2026)

Covariance test for discretely observed functional data: when and how it works?
by: Zhou, Yang, et al.
Published: (2025)

A doubly robust estimator for the Mann Whitney Wilcoxon Rank Sum Test when applied for causal inference in observational studies
by: Chen, Ruohui, et al.
Published: (2024)

Improving inverse probability of censoring weighting for win statistics with composite survival outcomes
by: Fang, Xi, et al.
Published: (2026)

On the permutation equivariance principle for causal estimands
by: Tong, Jiaqi, et al.
Published: (2025)

Bias in mixed models when analysing longitudinal data subject to irregular observation: when should we worry about it and how can recommended visit intervals help in specifying joint models when needed?
by: Garrett, Rose, et al.
Published: (2024)

Retrospective score tests versus prospective score tests for genetic association with case-control data
by: Liu, Yukun, et al.
Published: (2025)