联合混合分位数回归和事件时间分析

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY
G. Dagne
{"title":"联合混合分位数回归和事件时间分析","authors":"G. Dagne","doi":"10.1214/22-bjps537","DOIUrl":null,"url":null,"abstract":". Growth curve mixture models for longitudinal data are often developed on the conditional mean of a response, focusing only on the central section of the distribution. There is, however, an increasing desire to provide holistic information on different parts of the distribution of the response such as lower and higher quantiles. This article presents quantile regression analysis within the framework of growth curve models by jointly analyzing time to an event and longitudinal data with multiphasic features. The multiphasic patterns are accounted for at different quantiles by modeling heterogeneous growth trajectories which show gradual changes from a declining trend to an increasing trend over time within latent classes. Thus, we assess these important features of longitudinal data using bent-cable models along with a joint modeling of time to event process and response process. The proposed methods are illustrated using a real data set from an AIDS clinical study. model for assessing conditional quantiles of a response process with latent classes of growth trajectories and a time to event process. These processes were assessed by measuring the association between HIV viral load dynamics and time to first","PeriodicalId":51242,"journal":{"name":"Brazilian Journal of Probability and Statistics","volume":" ","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Joint mixture quantile regressions and time-to-event analysis\",\"authors\":\"G. Dagne\",\"doi\":\"10.1214/22-bjps537\",\"DOIUrl\":null,\"url\":null,\"abstract\":\". Growth curve mixture models for longitudinal data are often developed on the conditional mean of a response, focusing only on the central section of the distribution. There is, however, an increasing desire to provide holistic information on different parts of the distribution of the response such as lower and higher quantiles. This article presents quantile regression analysis within the framework of growth curve models by jointly analyzing time to an event and longitudinal data with multiphasic features. The multiphasic patterns are accounted for at different quantiles by modeling heterogeneous growth trajectories which show gradual changes from a declining trend to an increasing trend over time within latent classes. Thus, we assess these important features of longitudinal data using bent-cable models along with a joint modeling of time to event process and response process. The proposed methods are illustrated using a real data set from an AIDS clinical study. model for assessing conditional quantiles of a response process with latent classes of growth trajectories and a time to event process. These processes were assessed by measuring the association between HIV viral load dynamics and time to first\",\"PeriodicalId\":51242,\"journal\":{\"name\":\"Brazilian Journal of Probability and Statistics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2022-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Brazilian Journal of Probability and Statistics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1214/22-bjps537\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brazilian Journal of Probability and Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1214/22-bjps537","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0

摘要

纵向数据的增长曲线混合模型通常基于响应的条件平均值,只关注分布的中心部分。然而,人们越来越希望提供关于响应分布的不同部分的整体信息,例如较低和较高的分位数。本文在增长曲线模型的框架内,通过联合分析事件的时间和具有多相特征的纵向数据,提出了分位数回归分析。通过对异质增长轨迹进行建模,在不同的分位数上解释了多相模式,异质增长轨迹显示了潜在类别内随着时间的推移从下降趋势到增加趋势的逐渐变化。因此,我们使用弯曲电缆模型以及事件时间过程和响应过程的联合建模来评估纵向数据的这些重要特征。所提出的方法是使用艾滋病临床研究的真实数据集来说明的。用于评估具有潜在增长轨迹类别和事件时间过程的响应过程的条件分位数的模型。通过测量HIV病毒载量动态和首次感染时间之间的相关性来评估这些过程
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Joint mixture quantile regressions and time-to-event analysis
. Growth curve mixture models for longitudinal data are often developed on the conditional mean of a response, focusing only on the central section of the distribution. There is, however, an increasing desire to provide holistic information on different parts of the distribution of the response such as lower and higher quantiles. This article presents quantile regression analysis within the framework of growth curve models by jointly analyzing time to an event and longitudinal data with multiphasic features. The multiphasic patterns are accounted for at different quantiles by modeling heterogeneous growth trajectories which show gradual changes from a declining trend to an increasing trend over time within latent classes. Thus, we assess these important features of longitudinal data using bent-cable models along with a joint modeling of time to event process and response process. The proposed methods are illustrated using a real data set from an AIDS clinical study. model for assessing conditional quantiles of a response process with latent classes of growth trajectories and a time to event process. These processes were assessed by measuring the association between HIV viral load dynamics and time to first
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
1.60
自引率
10.00%
发文量
30
审稿时长
>12 weeks
期刊介绍: The Brazilian Journal of Probability and Statistics aims to publish high quality research papers in applied probability, applied statistics, computational statistics, mathematical statistics, probability theory and stochastic processes. More specifically, the following types of contributions will be considered: (i) Original articles dealing with methodological developments, comparison of competing techniques or their computational aspects. (ii) Original articles developing theoretical results. (iii) Articles that contain novel applications of existing methodologies to practical problems. For these papers the focus is in the importance and originality of the applied problem, as well as, applications of the best available methodologies to solve it. (iv) Survey articles containing a thorough coverage of topics of broad interest to probability and statistics. The journal will occasionally publish book reviews, invited papers and essays on the teaching of statistics.
×
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:481959085
Book学术官方微信