Practical implications of equating equivalence tests: Reply to Campbell and Gustafson (2022).

IF 7.6 1区 心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY
Maximilian Linde, Jorge N Tendeiro, Eric-Jan Wagenmakers, Don van Ravenzwaaij
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引用次数: 0

Abstract

Linde et al. (2021) compared the "two one-sided tests" the "highest density interval-region of practical equivalence", and the "interval Bayes factor" approaches to establishing equivalence in terms of power and Type I error rate using typical decision thresholds. They found that the interval Bayes factor approach exhibited a higher power but also a higher Type I error rate than the other approaches. In response, Campbell and Gustafson (2022) showed that the performances of the three approaches can approximate one another when they are calibrated to have the same Type I error rate. In this article, we argue that these results have little bearing on how these approaches are used in practice; a concrete example is used to highlight this important point. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

等效测试的实际意义:答复坎贝尔和古斯塔夫森(2022 年)。
Linde 等人(2021 年)比较了 "两个单边检验"、"最高密度区间-实际等效区域 "和 "区间贝叶斯因子 "方法,使用典型的决策阈值来确定等效的功率和 I 类错误率。他们发现,与其他方法相比,区间贝叶斯因子法显示出更高的功率,但 I 类错误率也更高。作为回应,Campbell 和 Gustafson(2022 年)表明,当这三种方法被校准为具有相同的 I 类错误率时,它们的性能可以相互接近。在本文中,我们认为这些结果与这些方法在实践中的应用关系不大;我们将通过一个具体的例子来强调这一点。(PsycInfo Database Record (c) 2024 APA, 版权所有)。
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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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