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间接实验的因果推断。

Causal inference from indirect experiments.

作者信息

Pearl J

机构信息

Computer Science Department, University of California, Los Angeles 90024, USA.

出版信息

Artif Intell Med. 1995 Dec;7(6):561-82. doi: 10.1016/0933-3657(95)00027-3.

DOI:10.1016/0933-3657(95)00027-3
PMID:8963376
Abstract

An indirect experiment is a study in which randomized control is replaced by randomized encouragement, that is, subjects are encouraged, rather than forced, to receive a given treatment program. The purpose of this paper is to bring to the attention of experimental researchers simple mathematical results that enable us to assess, from indirect experiments, the strength with which causal influences operate among variables of interest. The results reveal that despite the laxity of the encouraging instrument, data from indirect experimentation can yield significant and sometimes accurate information on the impact of a program on the population as a whole, as well as on the particular individuals who participated in the program.

摘要

间接实验是一种将随机对照替换为随机鼓励的研究,也就是说,鼓励受试者而非强迫他们接受特定的治疗方案。本文的目的是让实验研究人员注意到一些简单的数学结果,这些结果使我们能够从间接实验中评估感兴趣的变量之间因果影响的作用强度。结果表明,尽管鼓励手段较为宽松,但间接实验的数据仍可产生有关某个方案对总体人群以及参与该方案的特定个体的影响的重要且有时准确的信息。

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