The application of propensity score methods in observational studies

被引:0
作者
Zhao, Yuejuan [1 ]
机构
[1] Fudan Univ, Sch Data Sci, Shanghai, Peoples R China
关键词
propensity score; observational study; confounding variable; treatment effect; linear regression; REGRESSION;
D O I
10.3389/fams.2024.1384217
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Introduction In research, it is crucial to accurately estimate treatment effects and analyze experimental results. Common methods include comparing outcome differences between different groups and using linear regression models for analysis. However, observational studies may have significantly different distributions of confounding variables between control and treatment groups, leading to errors in estimating treatment effects.Methods The propensity score methods can address this issue by weighting or matching samples to approximate the scenario of a randomized experiment and allow for more accurate estimation of treatment this paper.Results We use propensity score methods to analyze three datasets from observational studies and draw conclusions different from those in the original text. Furthermore, we simulate three scenarios, and the results demonstrate the superiority of propensity score methods over methods such as linear regression in addressing selection bias.Discussion Therefore, it is essential to thoroughly consider the characteristics of the data and select appropriate methods to ensure reliable conclusions in practical data analysis.
引用
收藏
页数:9
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