The p-value Function and Statistical Inference

被引:23
|
作者
Fraser, D. A. S. [1 ]
机构
[1] Univ Toronto, Dept Stat Sci, 100 George St, Toronto, ON M5S 3G3, Canada
来源
AMERICAN STATISTICIAN | 2019年 / 73卷
基金
加拿大自然科学与工程研究理事会;
关键词
Accept-Reject; Ancillarity; Box-Cox; Conditioning; Decision or judgment; Discrete data; Extreme value model; Fieller-Creasy; Gamma mean; Percentile position; Power function; Statistical position; FORMULA; TESTS;
D O I
10.1080/00031305.2019.1556735
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
This article has two objectives. The first and narrower is to formalize the p-value function, which records all possible p-values, each corresponding to a value for whatever the scalar parameter of interest is for the problem at hand, and to show how this p-value function directly provides full inference information for any corresponding user or scientist. The p-value function provides familiar inference objects: significance levels, confidence intervals, critical values for fixed-level tests, and the power function at all values of the parameter of interest. It thus gives an immediate accurate and visual summary of inference information for the parameter of interest. We show that the p-value function of the key scalar interest parameter records the statistical position of the observed data relative to that parameter, and we the describe an accurate approximation to that p-value function which is readily constructed.
引用
收藏
页码:135 / 147
页数:13
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