Results 11 to 20 of about 206,310 (335)

Propensity score matching with R: conventional methods and new features

Annals of Translational Medicine, 2021
It is increasingly important to accurately and comprehensively estimate the effects of particular clinical treatments. Although randomization is the current gold standard, randomized controlled trials (RCTs) are often limited in practice due to ethical ...
Qin-yu Zhao, Jing-chao Luo, Ying Su, Yi-jie Zhang, G. Tu, Zhe Luo   +5 more
semanticscholar   +1 more source

Optimal caliper width for propensity score matching of three treatment groups: a Monte Carlo study. [PDF]

PLoS ONE, 2013
Propensity score matching is a method to reduce bias in non-randomized and observational studies. Propensity score matching is mainly applied to two treatment groups rather than multiple treatment groups, because some key issues affecting its application
Yongji Wang, Hongwei Cai, Chanjuan Li, Zhiwei Jiang, Ling Wang, Jiugang Song, Jielai Xia   +6 more
doaj   +1 more source

Adoption of improved agricultural technology and its impact on household income: a propensity score matching estimation in eastern Ethiopia

Agriculture & Food Security, 2021
Adoption of improved agricultural technologies remains to be a promising strategy to achieve food security and poverty reduction in many developing countries.
M. G. Wordofa, J. Y. Hassen, G. S. Endris, C. Aweke, D. Moges, Debbebe T. Rorisa   +5 more
semanticscholar   +1 more source

Risk of Alzheimer’s Disease Following Influenza Vaccination: A Claims-Based Cohort Study Using Propensity Score Matching

Journal of Alzheimer's Disease, 2022
Background: Prior studies have found a reduced risk of dementia of any etiology following influenza vaccination in selected populations, including veterans and patients with serious chronic health conditions.
Avram S. Bukhbinder, Yaobin Ling, Omar Hasan, Xiaoqian Jiang, Yejin Kim, Kamal Phelps, R. Schmandt, Albert Y. Amran, Ryan P. Coburn, Srivathsan Ramesh, Qian Xiao, P. Schulz   +11 more
semanticscholar   +1 more source

Genetic matching for time-dependent treatments: a longitudinal extension and simulation study

BMC Medical Research Methodology, 2023
Background Longitudinal matching can mitigate confounding in observational, real-world studies of time-dependent treatments. To date, these methods have required iterative, manual re-specifications to achieve covariate balance.
Deirdre Weymann, Brandon Chan, Dean A. Regier   +2 more
doaj   +1 more source

Comparison of Propensity Score Weighting Methods to Remove Selection Bias in Average Treatment Effect Estimates

Uluslararası Türk Eğitim Bilimleri Dergisi, 2023
In this Monte Carlo simulation study, the performance of six different propensity score methods implemented through weighting cases was investigated: inverse probability of treatment weighting, truncated inverse probability of treatment weighting ...
Sungur Gürel, Walter Lana Leite
doaj   +1 more source

An overview of propensity score matching methods for clustered data

Statistical Methods in Medical Research, 2022
Propensity score matching is commonly used in observational studies to control for confounding and estimate the causal effects of a treatment or exposure.
Benjamin Langworthy, Yujie Wu, Molin Wang   +2 more
semanticscholar   +1 more source

Evaluating the performance of propensity score matching based approaches in individual patient data meta-analysis

BMC Medical Research Methodology, 2021
Background Individual-patient data meta-analysis (IPD-MA) is an increasingly popular approach because of its analytical benefits. IPD-MA of observational studies must overcome the problem of confounding, otherwise biased estimates of treatment effect may
Fatema Tuj Johara, Andrea Benedetti, Robert Platt, Dick Menzies, Piret Viiklepp, Simon Schaaf, Edward Chan   +6 more
doaj   +1 more source

Applications of propensity score matching: a case series of articles published in [PDF]

Annals of Coloproctology, 2022
Propensity score matching (PSM) is an increasingly applied method of ensuring comparability between groups of interest. However, PSM is often applied unconditionally, without precise considerations.
Hwa Jung Kim
doaj   +1 more source

Propensity score matching for causal inference and reducing the confounding effects: statistical standard and guideline of Life Cycle Committee

Life Cycle, 2022
Since the development of research methodology, there has always been keen interest in developing the accuracy of the research by comparing covariates.
S. Lee, K. P. Acharya
semanticscholar   +1 more source