置信区间的概念和解释:如何克服 P 值的局限性

Umar Hussain, Farhad Ali Khattak
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引用次数: 0

摘要

由于缺乏资源,了解整个人口的估计值(平均值或比例)是不可行的。因此,我们依靠样本估计值来得出有关人口的结论。真实的人口估计值所处的数值范围称为置信区间(CI),它比单一估计值更可靠。对于描述性研究,可信区间应与点估计值(平均值或比例)一起报告。对于推断统计中的效应大小(平均差、几率比例、风险比等),应在 p 值的基础上加上 CI 值,以确定关联的强度和方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Concept and Interpretation of Confidence Interval: How to Overcome Limitations of P-value
Knowing the estimate (mean or proportion) for the whole population is not feasible due to a lack of resources. Therefore, we rely on a sample estimate to draw conclusions about the population. The range of values in which the true population estimate lies is called a confidence interval (CI) which is more reliable than single estimate. For descriptive studies, CIs should be reported along with the point estimate (mean or proportion). For effect sizes in inferential statistics (mean difference, odds ratio, risk ratio, etc.), the p-value should be supplemented with a CI for strength and direction of the association.
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