Changing statistical significance with the amount of information: The adaptive α significance level

被引：34
|
作者：
Perez, Maria-Eglee [1 ]
Pericchi, Luis Raul [1 ]
机构：
[1] Univ Puerto Rico, Dept Math, San Juan, PR 00936 USA
来源：
STATISTICS & PROBABILITY LETTERS | 2014年 / 85卷
关键词：
Significance principle; Posterior probability principle; Bayes-non-Bayes compromise; p-value calibration; Adaptive confidence level; SCHWARZ CRITERION; LINEAR-MODELS; P-VALUES; CALIBRATION; HYPOTHESES;
D O I：
10.1016/j.spl.2013.10.018
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
We put forward an adaptive alpha which changes with the amount of sample information. This calibration may be interpreted as a Bayes-non-Bayes compromise, and leads to statistical consistency. The calibration can also be used to produce confidence intervals whose size takes in consideration the amount of observed information. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码：20 / 24
页数：5
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