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学业成绩的因果分析。

Causal analysis of academic performance.

作者信息

Rao D C, Morton N E, Elston R C, Yee S

出版信息

Behav Genet. 1977 Mar;7(2):147-59. doi: 10.1007/BF01066003.

Abstract

Maximum likelihood methods are presented to test for the relations between causes and effects in linear path diagrams, without assuming that estimates of causes are free of error. Causal analysis is illustrated by published data of the Equal Educational Opportunity Survey, which show that American schools do not significantly modify socioeconomic differences in academic performance and that little of the observed racial difference in academic performance is causal. For two races differing by 15 IQ points, the differential if social class were randomized would be only about 3 points. The principle is stressed that a racial effect in a causal system may be environmental and that its etiology can be studied only by analysis of family resemblance in hybrid populations.

摘要

本文提出了极大似然法,用于检验线性路径图中因果关系,且不假定原因的估计无误差。通过《平等教育机会调查》的已发表数据说明了因果分析,该数据表明美国学校并未显著改变学业成绩方面的社会经济差异,且学业成绩中观察到的种族差异几乎没有因果关系。对于智商相差15分的两个种族,如果随机分配社会阶层,差异仅约为3分。强调了一个原则,即因果系统中的种族效应可能是环境性的,其病因只能通过分析混合群体中的家族相似性来研究。

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