A note on Type S/M errors in hypothesis testing

被引:11
|
作者
Lu, Jiannan [1 ]
Qiu, Yixuan [2 ]
Deng, Alex [1 ]
机构
[1] Microsoft Corp, Redmond, WA 98052 USA
[2] Purdue Univ, W Lafayette, IN 47907 USA
关键词
design calculation; monotonicity; p-value; power calculation; replication; reproducibility; statistical significance; PSYCHOLOGICAL SCIENCE;
D O I
10.1111/bmsp.12132
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Motivated by the recent replication and reproducibility crisis, Gelman and Carlin (2014, Perspect. Psychol. Sci., 9, 641) advocated focusing on controlling for Type S/M errors, instead of the classic Type I/II errors, when conducting hypothesis testing. In this paper, we aim to fill several theoretical gaps in the methodology proposed by Gelman and Carlin (2014, Perspect. Psychol. Sci., 9, 641). In particular, we derive the closed-form expression for the expected Type M error, and study the mathematical properties of the probability of Type S error as well as the expected Type M error, such as monotonicity. We demonstrate the advantages of our results through numerical and empirical examples.
引用
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页码:1 / 17
页数:17
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