文章基本信息

标题：Confidence Intervals for Effect Sizes: Applying Bootstrap Resampling.
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作者：Banjanovic, Erin S. ; Osborne, Jason W.
期刊名称：Practical Assessment, Research and Evaluation
印刷版ISSN：1531-7714
电子版ISSN：1531-7714
出版年度：2016
卷号：21
期号：5
页码：1
出版社：ERIC: Clearinghouse On Assessment and Evaluation
摘要：Confidence intervals for effect sizes (CIES) provide readers with an estimate of the strength of a reported statistic as well as the relative precision of the point estimate. These statistics offer more information and context than null hypothesis statistic testing. Although confidence intervals have been recommended by scholars for many years, these statistics are often not reported. This may be partially due to the complexity of calculating confidence intervals for many statistics. Bootstrap resampling can be used to easily estimate confidence intervals around almost any type of point estimate. The aim of this paper is to demonstrate this methodology using real-world data and to develop several simple principles around this methodology to guide readers in appropriate application.