ISSN 0439-755X
CN 11-1911/B
主办:中国心理学会
   中国科学院心理研究所
出版:科学出版社

心理学报 ›› 2025, Vol. 57 ›› Issue (6): 1108-1118.doi: 10.3724/SP.J.1041.2025.1108 cstr: 32110.14.2025.1108

• 争鸣 • 上一篇    

因果·影响·相关与预测辨析

温忠麟(), 马鹏(), 孟进, 王一帆   

  1. 华南师范大学心理应用研究中心/心理学院, 广州 510631
  • 收稿日期:2025-03-18 发布日期:2025-04-15 出版日期:2025-06-25
  • 通讯作者: 马鹏, E-mail: mapeng@m.scnu.edu.cn;
    温忠麟, E-mail: wenzl@scnu.edu.cn
  • 基金资助:
    国家自然科学基金项目(32171091);广东省脑认知与人的素质发展基础学科研究中心(2024B0303390003)

Distinguishing between causality, influence, correlation, and prediction

WEN Zhonglin(), MA Peng(), MENG Jin, WANG Yifan   

  1. Center for Studies of Psychological Application / School of Psychology, South China Normal University, Guangzhou 510631, China
  • Received:2025-03-18 Online:2025-04-15 Published:2025-06-25

摘要:

针对温忠麟等人(2024b)提出的影响关系, 葛枭语(2025)撰文提出下面质疑:(1)“影响关系”缺乏明确定义; (2)影响关系与因果关系区分不开; (3)不能因为因果目标无法达到便创设新目标; (4)所谓的影响关系应当称为“预测”。本文对此做出回应:(1)影响关系定义严密, 用的是“属加种差”的定义方法; (2)因果关系一定是影响关系, 但影响关系不一定是因果关系; (3)建立影响关系可以是非实验研究的一种目标, 优于仅仅建立相关关系; (4)预测是对变量关系的应用, 但不是关系本身, 与影响关系不相称。

关键词: 影响关系, 相关关系, 因果关系, 影响因素, 预测

Abstract:

Wen et al. (2024) discussed the following three issues: (1) explaining why it is inappropriate to understand influence relationship between variables as causal or correlation relationship, and then providing the definitions for two terms, influence relationship and influence factor; (2) summarizing several ways to find evidence for justifying the directionality when modeling the influence relationship. (3) categorizing multiple influence factors working together.

Ge (2025) questioned Wen et al.’s article as follows: (1) the concept of “influence relationship” is not clearly defined; (2) influence relationship and causal relationship are indistinguishable; (3) one cannot create a new goal just because the means cannot provide causal evidence for the goal of causality; (4) the so-called influence relationship should be called “prediction”. In response to these concerns, the present article offers clarifications and justifications.

First, the influence relationship has been rigorously defined by using a “Genus and Differentia” approach in Wen et al.’s paper. The influence relationship can be determined by using logical reasoning and statistical correlation testing. We also explain “correlation”, the genus concept of the influence relationship.

Furthermore, any causal relationship is the influence relationship, and the two are equivalent in studies through randomized controlled experiments, whereas in other contexts influence relationship may not necessarily be causal relationship. We provided easily understandable cases where the influence relationship was established but the causal relationship was not. It also presented and explained the status and role of proxy effects in those cases.

Beyond experimentation, establishing influence relationships is a suitable goal for investigation and research, which is better than the goal of establishing correlation. In statistics, any “correlation” can be used for “prediction”, and the direction of prediction can differ from the actual direction of the variable relationship. Prediction is essentially statistical inference based on the relationships between variables, but it is not the relationships themselves. Causality, influence, and correlation are all relationships between variables, whereas prediction concerns the application of variable relationships. Therefore, prediction is not an appropriate substitute for influence relationship.

Key words: influence relationship, correlation relationship, causal relationship, influence factor, prediction

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