Replication and p Intervals p Values Predict the Future Only Vaguely, but Confidence Intervals Do Much Better
Replication and p Intervals p Values Predict the Future Only Vaguely, but Confidence Intervals Do Much Better
复制标题
DOI：
10.1111/j.1745-6924.2008.00079.x
复制
发表时间：
2008-07-01
影响因子：
12.6
通讯作者：
Cumming, Geoff
中科院分区：
文献类型：
--
作者：
Cumming, Geoff
复制是科学的基础，因此统计分析应该提供关于复制的信息。由于p值在心理学统计分析中占据主导地位，因此询问p对复制有何影响很重要。这个问题的答案是“令人惊讶的少。在一个典型实验的25次重复模拟中，p从0.44变化。值得注意的是，无论样本大小如何，这个区间（称为p区间）都是这么宽。p是如此不可靠，并且给出了如此明显模糊的信息，以至于它是一个很差的推理基础。然而，置信区间提供了关于复制的更好的信息。研究人员应该通过使用置信区间和模型拟合技术以及采用元分析思维来最大限度地减少p的作用。
Replication is fundamental to science, so statistical analysis should give information about replication. Because p values dominate statistical analysis in psychology, it is important to ask what p says about replication. The answer to this question is "Surprisingly little." In one simulation of 25 repetitions of a typical experiment, p varied from .44. Remarkably, the interval-termed a p interval-is this wide however large the sample size. p is so unreliable and gives such dramatically vague information that it is a poor basis for inference. Confidence intervals, however, give much better information about replication. Researchers should minimize the role of p by using confidence intervals and modelfitting techniques and by adopting meta-analytic thinking.