复制时代对心理科学I型错误率的再思考。

IF 7.6 1区 心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY
Psychological methods Pub Date : 2024-04-01 Epub Date: 2022-04-11 DOI:10.1037/met0000490
Michael T Carlin, Mack S Costello, Madisyn A Flansburg, Alyssa Darden
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引用次数: 0

摘要

在设计实验时,仔细考虑I型和II型错误率之间的权衡对于最大限度地提高统计决策准确性至关重要。通常,在心理科学中,I型错误率(例如.05)显著低于II型错误率。此外,积极的发现(真实效果和I型错误)更有可能成为复制的焦点。这种传统方法导致非常高的II型错误率。分析表明,将I型错误率提高到.10,从而增加每次测试的功率并降低II型错误率,可以提高统计决策的总体正确率。I型错误率的增加与心理学中的复制和“新统计学”运动相一致,在这种情况下最为有益。(PsycInfo数据库记录(c)2022 APA,保留所有权利)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reconsideration of the type I error rate for psychological science in the era of replication.

Careful consideration of the tradeoff between Type I and Type II error rates when designing experiments is critical for maximizing statistical decision accuracy. Typically, Type I error rates (e.g., .05) are significantly lower than Type II error rates (e.g., .20 for .80 power) in psychological science. Further, positive findings (true effects and Type I errors) are more likely to be the focus of replication. This conventional approach leads to very high rates of Type II error. Analyses show that increasing the Type I error rate to .10, thereby increasing power and decreasing the Type II error rate for each test, leads to higher overall rates of correct statistical decisions. This increase of Type I error rate is consistent with, and most beneficial in the context of, the replication and "New Statistics" movements in psychology. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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来源期刊
Psychological methods
Psychological methods PSYCHOLOGY, MULTIDISCIPLINARY-
CiteScore
13.10
自引率
7.10%
发文量
159
期刊介绍: Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.
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