{"title":"细粒度效应大小。","authors":"John M Ferron, Megan S Kirby, Lodi Lipien","doi":"10.1037/spq0000634","DOIUrl":null,"url":null,"abstract":"To make transparent individuals' responses to intervention over time in the systematic review of single-case experimental designs, we developed a method of estimating and graphing fine-grained effect sizes. Fine-grained effect sizes are both case- and time-specific and thus provide more nuanced information than effect size estimates that average effects across time, across cases, or both. We demonstrate the method for estimating fine-grained effect sizes under three different baseline stability assumptions: outcome stability, level stability, and trend stability. We then use the method to graph individual effect trajectories from three single-case experimental design studies that examined the impact of self-management interventions on students identified with autism. We conclude by discussing limitations associated with estimating and graphing fine-grained effect sizes and directions for further development. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fine-grained effect sizes.\",\"authors\":\"John M Ferron, Megan S Kirby, Lodi Lipien\",\"doi\":\"10.1037/spq0000634\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To make transparent individuals' responses to intervention over time in the systematic review of single-case experimental designs, we developed a method of estimating and graphing fine-grained effect sizes. Fine-grained effect sizes are both case- and time-specific and thus provide more nuanced information than effect size estimates that average effects across time, across cases, or both. We demonstrate the method for estimating fine-grained effect sizes under three different baseline stability assumptions: outcome stability, level stability, and trend stability. We then use the method to graph individual effect trajectories from three single-case experimental design studies that examined the impact of self-management interventions on students identified with autism. We conclude by discussing limitations associated with estimating and graphing fine-grained effect sizes and directions for further development. (PsycInfo Database Record (c) 2024 APA, all rights reserved).\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1037/spq0000634\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/spq0000634","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
摘要
在对单病例实验设计进行系统回顾时，为了使个人对干预措施的反应随时间推移而变得透明，我们开发了一种估算细粒度效应大小并绘制其图表的方法。细粒度效应大小既针对特定病例，也针对特定时间，因此与跨时间、跨病例或两者平均效应的效应大小估算相比，能提供更细致入微的信息。我们演示了在三种不同的基线稳定性假设下估算细粒度效应大小的方法：结果稳定性、水平稳定性和趋势稳定性。然后，我们使用该方法绘制了三项单一案例实验设计研究的个体效应轨迹图，这些研究考察了自我管理干预措施对自闭症学生的影响。最后，我们讨论了与估计和绘制精细效应大小相关的局限性以及进一步发展的方向。(PsycInfo Database Record (c) 2024 APA, 版权所有）。
To make transparent individuals' responses to intervention over time in the systematic review of single-case experimental designs, we developed a method of estimating and graphing fine-grained effect sizes. Fine-grained effect sizes are both case- and time-specific and thus provide more nuanced information than effect size estimates that average effects across time, across cases, or both. We demonstrate the method for estimating fine-grained effect sizes under three different baseline stability assumptions: outcome stability, level stability, and trend stability. We then use the method to graph individual effect trajectories from three single-case experimental design studies that examined the impact of self-management interventions on students identified with autism. We conclude by discussing limitations associated with estimating and graphing fine-grained effect sizes and directions for further development. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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