The adoptr Package: Adaptive Optimal Designs for Clinical Trials in R

IF 5.4 2区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Statistical Software Pub Date : 2021-06-28 DOI:10.18637/jss.v098.i09
K. Kunzmann, Maximilian Pilz, Carolin Herrmann, G. Rauch, M. Kieser
{"title":"The adoptr Package: Adaptive Optimal Designs for Clinical Trials in R","authors":"K. Kunzmann, Maximilian Pilz, Carolin Herrmann, G. Rauch, M. Kieser","doi":"10.18637/jss.v098.i09","DOIUrl":null,"url":null,"abstract":"Even though adaptive two-stage designs with unblinded interim analyses are becoming increasingly popular in clinical trial designs, there is a lack of statistical software to make their application more straightforward. The package adoptr fills this gap for the common case of two-stage one- or two-arm trials with (approximately) normally distributed outcomes. In contrast to previous approaches, adoptr optimizes the entire design upfront which allows maximal efficiency. To facilitate experimentation with different objective functions, adoptr supports a flexible way of specifying both (composite) objective scores and (conditional) constraints by the user. Special emphasis was put on providing measures to aid practitioners with the validation process of the package.","PeriodicalId":17237,"journal":{"name":"Journal of Statistical Software","volume":"9 1","pages":""},"PeriodicalIF":5.4000,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistical Software","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.18637/jss.v098.i09","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 5

Abstract

Even though adaptive two-stage designs with unblinded interim analyses are becoming increasingly popular in clinical trial designs, there is a lack of statistical software to make their application more straightforward. The package adoptr fills this gap for the common case of two-stage one- or two-arm trials with (approximately) normally distributed outcomes. In contrast to previous approaches, adoptr optimizes the entire design upfront which allows maximal efficiency. To facilitate experimentation with different objective functions, adoptr supports a flexible way of specifying both (composite) objective scores and (conditional) constraints by the user. Special emphasis was put on providing measures to aid practitioners with the validation process of the package.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
采用者包:R临床试验的适应性优化设计
尽管采用非盲法中期分析的自适应两阶段设计在临床试验设计中越来越流行,但缺乏统计软件使其应用更直接。对于(近似)正态分布结果的两阶段单组或双组试验的常见情况,一揽子采用者填补了这一空白。与以前的方法相比,adoptr预先优化了整个设计,从而实现了最大的效率。为了方便不同目标函数的实验,adoptr支持一种灵活的方式来指定(复合)目标分数和(条件)约束。特别强调的是提供措施来帮助实践者进行包的验证过程。
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 去求助
来源期刊
Journal of Statistical Software
Journal of Statistical Software 工程技术-计算机:跨学科应用
CiteScore
10.70
自引率
1.70%
发文量
40
审稿时长
6-12 weeks
期刊介绍: The Journal of Statistical Software (JSS) publishes open-source software and corresponding reproducible articles discussing all aspects of the design, implementation, documentation, application, evaluation, comparison, maintainance and distribution of software dedicated to improvement of state-of-the-art in statistical computing in all areas of empirical research. Open-source code and articles are jointly reviewed and published in this journal and should be accessible to a broad community of practitioners, teachers, and researchers in the field of statistics.
期刊最新文献
spsurvey: Spatial Sampling Design and Analysis in R. Application of Equal Local Levels to Improve Q-Q Plot Testing Bands with R Package qqconf. Elastic Net Regularization Paths for All Generalized Linear Models. Broken Stick Model for Irregular Longitudinal Data jumpdiff: A Python Library for Statistical Inference of Jump-Diffusion Processes in Observational or Experimental Data Sets
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1