Confounder adjustment in observational comparative effectiveness researches: (1) statistical adjustment approaches for measured confounder
10.3760/cma.j.issn.0254-6450.2019.10.024
- VernacularTitle: 如何控制观察性疗效比较研究中的混杂因素：（一）已测量混杂因素的统计学分析方法
- Author:
Lihong HUANG
1
;
Yongyue WEI
2
;
Feng CHEN
2
Author Information
1. Department of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
2. Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
- Publication Type:Journal Article
- Keywords:
Observational comparative effectiveness research;
Real world study;
Measured confounder;
Adjustment;
Statistical method
- From:
Chinese Journal of Epidemiology
2019;40(10):1304-1309
- CountryChina
- Language:Chinese
-
Abstract:
Observational comparative effectiveness studies have been widely conducted to provide evidence on additional effectiveness and to support randomized controlled findings in research. Although this type of study becomes more important over time, challenges related to the common biases which stemmed from confounders, are difficult to control. This manuscript summarizes some statistical methods used on adjusting measured confounders that often noticed in research, regarding the observational comparative effectiveness. Useful traditional methods would include stratified analysis, paired analysis, covariate model and multivariable model, etc.. Unconventional adjustment approaches such as propensity score and disease risk score methods may also be used in studies, for matching, stratification and adjustment. A good study design should be able to control confounders. The limitations of all the post hoc statistical adjustment methods should also be fully understood before being appropriately applied in practical events.
