辛普森悖论与实验研究。
Simpson's paradox and experimental research.
作者信息
Ameringer Suzanne, Serlin Ronald C, Ward Sandra
机构信息
Virginia Commonwealth University, 1100 East Leigh Street, Richmond, VA 23219, USA.
出版信息
Nurs Res. 2009 Mar-Apr;58(2):123-7. doi: 10.1097/NNR.0b013e318199b517.
BACKGROUND
Experimental research in nursing has increased considerably in recent years. To improve the quality of such research, it is critical to reduce threats to internal validity. One threat that has received inadequate attention in the nursing literature is Simpson's paradox--a case of extreme confounding that can lead to erroneous conclusions about the effects of an experimental intervention. In fact, it can lead to a conclusion about an intervention effect that is the opposite of the correct inference.
APPROACH
The aims of this study were to describe Simpson's paradox, provide a hypothetical example, and discuss approaches to avoiding the paradox.
RESULTS
The paradox is due to the combination of an overlooked confounding variable and a disproportionate allocation of that variable among experimental groups. Different designs and analysis approaches that can be used to avoid the paradox are presented.
DISCUSSION
Simpson's paradox can be avoided by selecting an appropriate experimental design and analysis that incorporates the confounding variable in such a way as to obtain unconfounded estimates of treatment effects, thus more accurately answering the research question.
背景
近年来，护理领域的实验研究有了显著增加。为提高此类研究的质量，减少对内部效度的威胁至关重要。护理文献中未得到充分关注的一个威胁是辛普森悖论——一种极端的混杂情况，可能导致关于实验干预效果的错误结论。事实上，它可能导致得出与正确推断相反的干预效果结论。
方法
本研究的目的是描述辛普森悖论，提供一个假设示例，并讨论避免该悖论的方法。
结果
该悖论是由于一个被忽视的混杂变量与该变量在实验组之间的不均衡分配共同作用所致。文中介绍了可用于避免该悖论的不同设计和分析方法。
讨论
通过选择合适的实验设计和分析方法，将混杂变量纳入其中以获得无偏倚的治疗效果估计，从而更准确地回答研究问题，就可以避免辛普森悖论。
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