The fallacy of placing confidence in confidence intervals

被引：0
作者：
Richard D. Morey
Rink Hoekstra
Jeffrey N. Rouder
Michael D. Lee
Eric-Jan Wagenmakers
机构：
[1] Cardiff University,
[2] University of Groningen,undefined
[3] University of Missouri,undefined
[4] University of California-Irvine,undefined
[5] University of Amsterdam,undefined
来源：
Psychonomic Bulletin & Review | 2016年 / 23卷
关键词：
Bayesian inference and parameter estimation; Bayesian statistics; Statistical inference; Statistics;
D O I：
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中图分类号：
学科分类号：
摘要：
Interval estimates – estimates of parameters that include an allowance for sampling uncertainty – have long been touted as a key component of statistical analyses. There are several kinds of interval estimates, but the most popular are confidence intervals (CIs): intervals that contain the true parameter value in some known proportion of repeated samples, on average. The width of confidence intervals is thought to index the precision of an estimate; CIs are thought to be a guide to which parameter values are plausible or reasonable; and the confidence coefficient of the interval (e.g., 95 %) is thought to index the plausibility that the true parameter is included in the interval. We show in a number of examples that CIs do not necessarily have any of these properties, and can lead to unjustified or arbitrary inferences. For this reason, we caution against relying upon confidence interval theory to justify interval estimates, and suggest that other theories of interval estimation should be used instead.
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页码：103 / 123
页数：20
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