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Propensity score analysis methods with balancing constraints: A Monte Carlo study
Statistical Methods in Medical Research, 2021 The inverse probability weighting is an important propensity score weighting method to estimate the average treatment effect. Recent literature shows that it can be easily combined with covariate balancing constraints to reduce the detrimental effects of
Yan Li, Liang Li
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BMC Public Health, 2019 Background Since economic inequality is often accompanied by health inequalities, health care inequalities are increasingly becoming a hot issue on a global scale. As a developing country, China is still facing the same problems as other countries in the
Wei Xian +6 more
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Multivariate Behavioral Research, 2021 Propensity score methods are a widely recommended approach to adjust for confounding and to recover treatment effects with non-experimental, single-level data.
Alvaro Fuentes, O. Lüdtke, A. Robitzsch
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Jambura Journal of MathematicsResearch on complications of Diabetes Mellitus (DM) is multifactorial, where the risk factors causing DM complications are interrelated, leading to confounding bias, which results in inaccurate research findings. Confounding bias can be reduced using the
Ingka Rizkyani Akolo +2 more
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Estimating the Causal Effect of Two-Dose COVID-19 Vaccination on Hospitalization Rates [PDF]
Epidemiology and Health System JournalBackground and aims: COVID-19 remains a global health challenge, with vaccination crucial for reducing severe cases. This study evaluated a two-dose COVID-19 vaccine’s effectiveness in lowering hospitalization rates using advanced statistical techniques.
Mahboobeh Taherizadeh +3 more
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Propensity score weighting under limited overlap and model misspecification [PDF]
Statistical Methods in Medical Research, 2020 Propensity score weighting methods are often used in non-randomized studies to adjust for confounding and assess treatment effects. The most popular among them, the inverse probability weighting, assigns weights that are proportional to the inverse of ...
Yunji Zhou +2 more
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Specification tests for the propensity score [PDF]
Journal of Econometrics, 2019 This paper proposes new nonparametric diagnostic tools to assess the asymptotic validity of different treatment effects estimators that rely on the correct specification of the propensity score. We derive a particular restriction relating the propensity score distribution of treated and control groups, and develop specification tests based upon it. The
Sant'Anna, Pedro H. C., Song, Xiaojun
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Subgroup balancing propensity score [PDF]
Statistical Methods in Medical Research, 2019 This paper concerns estimation of subgroup treatment effects with observational data. Existing propensity score methods are mostly developed for estimating overall treatment effect. Although the true propensity scores balance covariates in any subpopulations, the estimated propensity scores may result in severe imbalance in subgroup samples.
Jing Dong +3 more
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Propensity Score Analysis with Survey Weighted Data
Journal of Causal Inference, 2015 Propensity score analysis (PSA) is a common method for estimating treatment effects, but researchers dealing with data from survey designs are generally not properly accounting for the sampling weights in their analyses.
Ridgeway Greg +3 more
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Emerging Themes in Epidemiology, 2010 Purpose To control for confounding bias from non-random treatment assignment in observational data, both traditional multivariable models and more recently propensity score approaches have been applied.
Hunink MG Myriam +4 more
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