基于大数据元分析的调节效应识别:基础模型与实证检验
Identifying Moderation Effects via Meta-Analysis of Big Data:Basic Model and Empirical Testing
林伟杰 1周文杰 2魏志鹏 3杨克虎3
作者信息
- 1. 北京交通大学经济管理学院,北京 100044
- 2. 中国人民大学信息资源管理学院,北京 100080;西北师范大学商学院,兰州 730070;兰州大学循证社会科学交叉创新实验室,兰州 730030
- 3. 兰州大学基础医学院循证医学中心,兰州 730030;兰州大学循证社会科学交叉创新实验室,兰州 730030
- 折叠
摘要
作为实证研究中识别因果关系的一种重要方法,调节效应检验有助于揭示自变量和因变量之间的深层次关系,然而该方法存在无法获得真实效应值且外部效度低等问题.受限于原始研究与生俱来的缺陷,循证领域亟待发展出新的调节效应识别模型.本研究采用大数据循证理念,利用循环方法对控制变量进行排列组合,从而模拟了"穷尽"所有可能的原始研究设计,对全部可能的变量间关系进行了回归分析并记录所有效应值.进而,使用元分析法对全部原始效应量进行全覆盖式合并,以获得真实的效应值,以此提升调节效应结果的外部效度.最后,本研究以信息贫困研究为例,详细展示了大数据循证视角下调节效应识别的所有流程.本研究的主要贡献在于完善了大数据循证理念下的元分析方法体系,从大量原始研究效应中提取了真实效应值,提高了调节效应的外部效度与因果关系识别的可靠性.
Abstract
Moderation effect testing,as an important method for identifying causal relationships in empirical research,helps uncover underlying relationships between independent and dependent variables.However,this method suffers from issues such as the inability to obtain true effect values and low external validity.Owing to the limitations imposed by the inherent flaws of primary studies,the evidence-based field urgently needs new models for identifying moderation effects.In this study,we adopt the concept of big data evidence and use a recursive method to systematically arrange and combine control variables,thereby simulating the"exhaustion"of all possible original research designs.We conduct regression anal-yses and record all effect values for all possible variable relationships,and then use meta-analysis to comprehensively merge all original effect sizes to obtain true effect values and enhance the external validity of moderation effect results.Fi-nally,taking research on information poverty as an example,this study demonstrates in detail the entire process of identify-ing moderation effects from a big data evidence perspective.The main contribution of this paper is the enhancement of the meta-analysis framework within the realm of big data evidence-based approach.This involves distilling authentic effect siz-es from an extensive compilation of original research findings,thereby augmenting the external validity of moderating ef-fects and enhancing the dependability of causal inference.
关键词
大数据元分析/调节效应/循证社会科学/因果关系Key words
big data meta-analysis/moderation effect/evidence-based social science/causal relationship引用本文复制引用
基金项目
国家社会科学基金重大项目(19ZDA142)
出版年
2024
NETL
NSTL
万方数据