Methods in causal inference. Part 4: confounding in experiments

被引：1

作者：

Bulbulia, Joseph A. ^{[1
]}

机构：

[1] Victoria Univ Wellington, Wellington, New Zealand

来源：

EVOLUTIONARY HUMAN SCIENCES | 2024年 / 6卷

关键词：

Causal inference; experiments; DAGs; evolution; per protocol effect; intention to treat effect; RCT;

D O I：

10.1017/ehs.2024.34

中图分类号：

Q98 [人类学];

学科分类号：

030303 ;

摘要：

Confounding bias arises when a treatment and outcome share a common cause. In randomised controlled experiments (trials), treatment assignment is random, ostensibly eliminating confounding bias. Here, we use causal directed acyclic graphs to unveil eight structural sources of bias that nevertheless persist in these trials. This analysis highlights the crucial role of causal inference methods in the design and analysis of experiments, ensuring the validity of conclusions drawn from experimental data.

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页数：10

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