propensity-score matched analysispropensity-score matched analysis 倾向性评分匹配(propensity score matching,PSM)是一种统计学方法,旨在减少研究中的偏差和混杂变量影响,以便对观察组和对照组进行更合理的比较。这种方法最早由Paul Rosenbaum和Donald Rubin在1983年提出,此后获得了快速发展并且在各个方面不断改进。 倾向...
缺点是工具变量选取难度大,且易引起选择偏倚。 5.倾向得分匹配法(Propensity Score Matched) 采用多个配对变量跟分组变量建立回归方程,根据方程每个研究对象算出一个值作为得分(score),评分相近的研究对象匹配。可用于观察性研究:队列研究设计,分组变量是暴露因素X;病例对照研究设计,分组变量是结局指标Y。PSM优点:提高论...
MIPD cases were analyzed intention-to-treat, regardless of conversion to open surgery, and matched in a 1:1 ratio to OPD controls based on the propensity score with a standard caliper width of 0.2. 告诉读者几件事情: 1、数据分析采用了意向治疗原则,微创转开腹患者,算微创;回顾性研究采用意向治疗...
最佳匹配形成pair的过程是minimize the total within-pair difference of propensity score最小化倾向性得分的配对内总差异,即全局优化。 但是这两者在生成平衡匹配样本(balanced matched samples)上效果基本相当。 (3)相似度度量:Nearest Neighbor v.s Caliper distance nearest neighbor matching就是在选择score与当前trea...
Of 785 patients with under-recognition of AKI and 616 patients with timely-recognition of AKI were propensity matched in a 1:1 ratio. The two groups, with a total of 482 matched patients (241:241), were comparable in baseline covariates. Under-recognition of AKI was not associated with 30...
当选择matched的控制组集合时,需要考虑: variables to be used for matching: covariates or propensity score distances the number of controls: pair-matching or multiple matching caliper: a chosen threshold of matching stratification: 即两阶段的matching ...
matched.by = "pscore", setseed = 12345) #利用ps.match函数进行倾向评分匹配,who.treated =1,表示1代表处理组,ratio确定匹配比例,x代表得分容差,givenTmatchingC = T表示用未处理记录去匹配处理组记录。 输入:summary(mydata.match) 结果:...
propensity score-matched cohorts 词典结果 propensity score-matched cohorts 倾向得分匹配的同伙
A meta-analysis pooling survival curves in randomized controlled trials and propensity-score matched studies of endovascular versus open abdominal aortic a... Regarding mid-to-long-term survival following elective endo-vascular aneurysm repair (EVAR) versus open surgical repair (OSR) for non-ruptured...
Note: A variance ratio of 1 in matched sample indicates a good matching, and a variance ratio below 2 is generally acceptable. bal.tab(m.out,v.threshold=2) ## Call ## matchit(formula = Treat ~ Xcont.1 + Xcont.2 + Xcat.1 + Xcat.2, ...