完整後設資料紀錄
DC 欄位語言
dc.contributor.authorShieh, Gwowenen_US
dc.date.accessioned2019-04-02T05:59:36Z-
dc.date.available2019-04-02T05:59:36Z-
dc.date.issued2018-09-01en_US
dc.identifier.issn1046-1310en_US
dc.identifier.urihttp://dx.doi.org/10.1007/s12144-016-9549-5en_US
dc.identifier.urihttp://hdl.handle.net/11536/147926-
dc.description.abstractAs a generalization of the standardized mean difference between two independent populations, two different effect size measures have been proposed to represent the degree of disparity among several treatment groups. One index relies on the standard deviation of the standardized means and the second formula is the range of the standardized means. Despite the obvious usage of the two measures, the associated test procedures for detecting a minimal important difference among standardized means have not been well explicated. This article reviews and compares the two approaches to testing the hypothesis that treatments have negligible effects rather than that of no difference. The primary emphasis is to reveal the underlying properties of the two methods with regard to power behavior and sample size requirement across a variety of design configurations. To enhance the practical usefulness, a complete set of computer algorithms for calculating the critical values, p-values, power levels, and sample sizes is also developed.en_US
dc.language.isoen_USen_US
dc.subjectEffect sizeen_US
dc.subjectPoweren_US
dc.subjectSample sizeen_US
dc.subjectStandardized mean differenceen_US
dc.titleOn Detecting a Minimal Important Difference among Standardized Meansen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s12144-016-9549-5en_US
dc.identifier.journalCURRENT PSYCHOLOGYen_US
dc.citation.volume37en_US
dc.citation.spage640en_US
dc.citation.epage647en_US
dc.contributor.department管理科學系zh_TW
dc.contributor.departmentDepartment of Management Scienceen_US
dc.identifier.wosnumberWOS:000440111500019en_US
dc.citation.woscount0en_US
顯示於類別:期刊論文