Topic Set Size Design and Power Analysis in Practice

T. Sakai
{"title":"Topic Set Size Design and Power Analysis in Practice","authors":"T. Sakai","doi":"10.1145/2970398.2970443","DOIUrl":null,"url":null,"abstract":"Topic set size design methods provide principles and procedures for test collection builders to decide on the number of topics to create. These methods can then help us keep improving the test collection design based on accumulated data. Simple Excel tools are available for such purposes. Post-hoc power analysis tools, available as simple R scripts, can help IR researchers examine the achieved power of a reported experiment and determine future sample sizes for ensuring high power. Thus, for example, underpowered user experiments can be detected, and a larger sample size can be proposed. If used appropriately, these Excel and R tools should be able to provide the IR community with better experimentation practices. The main objective of this tutorial is to let IR researchers familiarise themselves with these tools and understand the basic ideas behind them.","PeriodicalId":443715,"journal":{"name":"Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2970398.2970443","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

Topic set size design methods provide principles and procedures for test collection builders to decide on the number of topics to create. These methods can then help us keep improving the test collection design based on accumulated data. Simple Excel tools are available for such purposes. Post-hoc power analysis tools, available as simple R scripts, can help IR researchers examine the achieved power of a reported experiment and determine future sample sizes for ensuring high power. Thus, for example, underpowered user experiments can be detected, and a larger sample size can be proposed. If used appropriately, these Excel and R tools should be able to provide the IR community with better experimentation practices. The main objective of this tutorial is to let IR researchers familiarise themselves with these tools and understand the basic ideas behind them.
主题集大小设计与功效分析的实践
主题集大小设计方法为测试集合构建者决定要创建的主题数量提供了原则和过程。这些方法可以帮助我们在积累数据的基础上不断改进测试集设计。简单的Excel工具可用于此目的。事后功率分析工具,作为简单的R脚本,可以帮助IR研究人员检查所报告的实验的实现功率,并确定未来的样本量,以确保高功率。因此,例如,可以检测到动力不足的用户实验,并且可以提出更大的样本量。如果使用得当,这些Excel和R工具应该能够为IR社区提供更好的实验实践。本教程的主要目的是让IR研究人员熟悉这些工具并理解它们背后的基本思想。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信