Trafimow David
Department of Psychology, MSC 3452, PO Box 30001, New Mexico State University, Las Cruces, NM 88003-8001, USA.
Genet Soc Gen Psychol Monogr. 2006 Aug;132(3):215-39. doi: 10.3200/mono.132.3.215-240.
An ever-increasing proportion of social psychology researchers use various versions of complex correlational models such as path analyses or structural equation models and others to draw causal conclusions from correlational data. Critics of complex correlational models have pointed out that (a) misspecification errors are the rule rather than the exception, (b) one cannot draw causal conclusions from a set of correlations, (c) most researchers fail to adjust their correlations for attenuation due to unreliability, and (d) the measures researchers use may actually be measures of outside variables that are correlated with other variables in one's model. Rather than rehash the debates that go along with these criticisms, the author makes some assumptions that are extremely favorable to the complex correlational modeler in that all of these criticisms are disallowed. Nevertheless, even with these assumptions, the author shows how spurious direct and indirect effects are likely to be created by moderately valid measures when researchers compute complex correlations. The author concludes that until social psychologists are better able to deal with the issue of the validity of their measures, they should not use complex correlational models.
越来越多的社会心理学研究者使用各种复杂的相关模型，如路径分析或结构方程模型等的不同版本，以便从相关数据中得出因果结论。复杂相关模型的批评者指出：（a）错误设定误差是常态而非例外；（b）不能从一组相关性中得出因果结论；（c）大多数研究者没有针对因不可靠性导致的衰减对相关性进行调整；（d）研究者使用的测量方法实际上可能是与模型中其他变量相关的外部变量的测量。作者并未重复伴随这些批评而来的争论，而是做出了一些对复杂相关模型构建者极为有利的假设，即不允许所有这些批评存在。然而，即便有这些假设，作者仍展示了在研究者计算复杂相关性时，适度有效的测量方法如何可能产生虚假的直接和间接效应。作者得出结论，在社会心理学家能够更好地处理其测量方法的有效性问题之前，他们不应使用复杂相关模型。
