Results Under model misspecification conditions, propensity score methods had better robustness than model based methods.
结果当存在模型误定时，倾向指数方法比基于模型的方法具有较好的稳健性。
Objective Through introduction of principal theory and algorithm of propensity score to design SAS macro programs for binary data.
目的实例介绍倾向评分法的基本原理和适用条件，设计适用于分析二分类资料的SAS宏程序。
Conclusion For large and complicated data, propensity score methods had more flexibility in practical use than model based methods.
结论对于大量、关系复杂的数据，应用倾向指数方法具有较大的灵活性。
Similarly, when the cohort was divided into propensity score quintiles, we did not find a difference in survival between the two groups.
同样，当将队列划分成倾向分数五分数时，研究并未发现两组间生存率的差异。
We used propensity score analysis to adjust for potential differences in baseline characteristics of patients in the two treatment groups.
我们使用倾向评分分析，以调整两个治疗组中患者基线特征的潜在差异。
Objective to evaluate the statistical property of the estimators on exposure effect and value of propensity score methods in practical use.
目的评价由倾向指数方法得到的暴露效果的估计量和统计性质，并探讨其实用性。
The paper USES the propensity score-matching method to estimate the effects on training on rural labor's earnings based on micro data of Jilin Province in 2006.
基于2006年吉林省进城务工人员调查数据，采用倾向分匹配法对农民工的培训收入效应进行估算。
This paper uses the propensity score matching method to solve the endogenous problem effectively, basing on the panel data of listed companies from 2005 to 2012.
基于2005—2012年上市公司的面板数据，本文采用倾向评分匹配的方法，有效解决了样本“内生性”问题。
Objective Propose a method that combines the propensity score approach and non-parametric survival analysis for hazard ratio estimation in non-randomized medical researches.
目的提出一种适用于非随机化医学研究的，结合倾向指数与非参数生存分析估计风险比的方法。
Multivariate mixed models incorporating a propensity score to account for imbalance among cohorts were used to estimate drug effects on mortality with associated 95% confidence intervals (95%CI).
运用多变量混合摸型，加上说明不同队列间不均衡性的倾向评分，使用95%可信区间估计药物作用对死亡率的影响。
We will explore new methods that combine spatial econometric techniques and methods used in the program evaluation literature such as difference-in-differences and propensity score matching methods.
我们将探索把空间经济学技术和那些被用在项目评估文学中的方法结合起来的新方法，如“异中求异”的方法和倾向匹配划分方法。
We will explore new methods that combine spatial econometric techniques and methods used in the program evaluation literature such as difference-in-differences and propensity score matching methods.
我们将探索把空间经济学技术和那些被用在项目评估文学中的方法结合起来的新方法，如“异中求异”的方法和倾向匹配划分方法。
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