Formation of study population for causal inference
10.3760/cma.j.cn112338-20200612-00839
- VernacularTitle:因果推断中研究人群的形成
- Author:
Miao ZHANG
1
;
Yimin ZHU
;
Yaxin LI
;
Yutong MOU
;
Hui KAN
;
Wei FAN
;
Jianghong DAI
;
Yingjie ZHENG
Author Information
1. 复旦大学公共卫生学院流行病学教研室/国家卫生健康委员会卫生技术评估重点实验室（复旦大学）/复旦大学公共卫生学院公共卫生安全教育部重点实验室，上海 200032
- Keywords:
Causal thinking;
Study population;
Causal inference;
Cross-section;
Longitudinal;
Research design
- From:
Chinese Journal of Epidemiology
2021;42(7):1292-1298
- CountryChina
- Language:Chinese
-
Abstract:
Epidemiological analysis describes and compares the characteristics of a certain number of people to make causal inferences. The formation of the study population is always the first step. In this paper, we first define the concepts of cross-sections at both individual level and population level and introduce the three assumptions needed in the measurements in observational studies, i. e. the true values of the attributes are stable with time, the attribute variables are independent and the individuals are independent during the measuring process. We also determine that the causal inference research should be unified based on the time of the occurrence or beginning of a postulated cause, or exposure, should be in. Then, based on the dual roles of the population cross-section with causal thinking, we propose that research designs can be classified into two types with different characteristics: history reconstruction research and future exploration research. Finally, we briefly analyze the research design framework and the relationship between estimated effects and different designs. The discussion of the formation of a study population from the perspective of causal thinking can make a foundation for the classification of causal inference research design with appropriate effect parameters, which needs to be further studied.
