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关于被试内设计的置信区间

On confidence intervals for within-subjects designs.

作者信息

Blouin David C, Riopelle Arthur J

机构信息

Department of Experimental Statistics, Louisiana State University, Baton Rouge, LA 70803, USA.

出版信息

Psychol Methods. 2005 Dec;10(4):397-412. doi: 10.1037/1082-989X.10.4.397.

Abstract

Confidence intervals (CIs) for means are frequently advocated as alternatives to null hypothesis significance testing (NHST), for which a common theme in the debate is that conclusions from CIs and NHST should be mutually consistent. The authors examined a class of CIs for which the conclusions are said to be inconsistent with NHST in within-subjects designs and a class for which the conclusions are said to be consistent. The difference between them is a difference in models. In particular, the main issue is that the class for which the conclusions are said to be consistent derives from fixed-effects models with subjects fixed, not mixed models with subjects random. Offered is mixed model methodology that has been popularized in the statistical literature and statistical software procedures. Generalizations to different classes of within-subjects designs are explored, and comments on the future direction of the debate on NHST are offered.

摘要

均值的置信区间(CIs)常被提倡作为零假设显著性检验(NHST)的替代方法,在这场辩论中一个共同的主题是,置信区间和零假设显著性检验的结论应该相互一致。作者研究了一类在被试内设计中其结论据称与零假设显著性检验不一致的置信区间,以及一类其结论据称是一致的置信区间。它们之间的差异在于模型的不同。具体而言,主要问题在于,其结论据称一致的那一类置信区间源自被试固定的固定效应模型,而非被试随机的混合模型。本文提供了在统计文献和统计软件程序中已得到推广的混合模型方法。探讨了对不同类别的被试内设计的推广,并对零假设显著性检验辩论的未来方向提出了评论。

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