Correlation and Causation in the Study of Personality

被引:48
|
作者
Lee, James J. [1 ]
机构
[1] Harvard Univ, Dept Psychol, Cambridge, MA 02138 USA
关键词
personality; causality; directed acyclic graph; structural equation modelling; behavioural genetics; GENOME-WIDE ASSOCIATION; MISSING DATA; PATH MODELS; LOCI; INDIVIDUALS; VARIANTS; DIAGRAMS; GENETICS; SAMPLE; LIFE;
D O I
10.1002/per.1863
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Personality psychology aims to explain the causes and the consequences of variation in behavioural traits. Because of the observational nature of the pertinent data, this endeavour has provoked many controversies. In recent years, the computer scientist Judea Pearl has used a graphical approach to extend the innovations in causal inference developed by Ronald Fisher and Sewall Wright. Besides shedding much light on the philosophical notion of causality itself, this graphical framework now contains many powerful concepts of relevance to the controversies just mentioned. In this article, some of these concepts are applied to areas of personality research where questions of causation arise, including the analysis of observational data and the genetic sources of individual differences. Copyright (c) 2012 John Wiley & Sons, Ltd.
引用
收藏
页码:372 / 390
页数:19
相关论文
共 50 条