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Bayesian Random-Effects Meta-Analysis Integrating Individual Participant Data and Aggregate Data 整合个体参与者数据和总体数据的贝叶斯随机效应元分析
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2025-07-03 DOI: 10.1080/01621459.2025.2520469
Yunxiang Huang, Hang J. Kim, Chiung-Yu Huang, Mi-Ok Kim
{"title":"Bayesian Random-Effects Meta-Analysis Integrating Individual Participant Data and Aggregate Data","authors":"Yunxiang Huang, Hang J. Kim, Chiung-Yu Huang, Mi-Ok Kim","doi":"10.1080/01621459.2025.2520469","DOIUrl":"https://doi.org/10.1080/01621459.2025.2520469","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"267 1","pages":"1-21"},"PeriodicalIF":3.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Global and Episode-Specific Prediction of Recurrent Events Using Longitudinal Health Informatics Data. 利用纵向健康信息学数据对复发事件进行全球和特定事件预测。
IF 3 1区 数学
Journal of the American Statistical Association Pub Date : 2025-07-03 DOI: 10.1080/01621459.2025.2497569
Yifei Sun, Sy Han Chiou, Chiung-Yu Huang
{"title":"Global and Episode-Specific Prediction of Recurrent Events Using Longitudinal Health Informatics Data.","authors":"Yifei Sun, Sy Han Chiou, Chiung-Yu Huang","doi":"10.1080/01621459.2025.2497569","DOIUrl":"https://doi.org/10.1080/01621459.2025.2497569","url":null,"abstract":"<p><p>Accurate prediction of recurrent clinical events is crucial for effective management of chronic conditions such as cancer and cardiovascular disease. In recent years, longitudinal health informatics databases, which routinely collect data on repeated clinical events, have been increasingly utilized to construct risk prediction models. We introduce a novel nonparametric framework to predict recurrent events on a gap time scale using survival tree ensembles. Our framework incorporates two predictive modeling strategies: episode-specific model and global model. These models avoid strong assumptions on how future event risk depends on previous event history and other predictors, making them a promising alternative to Cox-type models. Additional complexities in tree-based prediction for recurrent events include induced informative censoring of gap times and inter-event correlations. We develop algorithms to address these issues through the use of inverse probability of censoring weighting and modified resampling procedures. Applied to SEER-Medicare data to predict repeated hospitalizations for breast cancer patients, our models showed superior performance. In particular, borrowing information across events via global models substantially improved prediction accuracy for later hospitalizations.</p>","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12363995/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144958720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
High-dimensional covariance regression with application to co-expression QTL detection 高维协方差回归及其在共表达QTL检测中的应用
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2025-07-03 DOI: 10.1080/01621459.2025.2520996
Rakheon Kim, Jingfei Zhang
{"title":"High-dimensional covariance regression with application to co-expression QTL detection","authors":"Rakheon Kim, Jingfei Zhang","doi":"10.1080/01621459.2025.2520996","DOIUrl":"https://doi.org/10.1080/01621459.2025.2520996","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"48 1","pages":"1-23"},"PeriodicalIF":3.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Debiasing Watermarks for Large Language Models via Maximal Coupling 基于最大耦合的大型语言模型水印去偏
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2025-07-03 DOI: 10.1080/01621459.2025.2520455
Yangxinyu Xie, Xiang Li, Tanwi Mallick, Weijie Su, Ruixun Zhang
{"title":"Debiasing Watermarks for Large Language Models via Maximal Coupling","authors":"Yangxinyu Xie, Xiang Li, Tanwi Mallick, Weijie Su, Ruixun Zhang","doi":"10.1080/01621459.2025.2520455","DOIUrl":"https://doi.org/10.1080/01621459.2025.2520455","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"104 1","pages":"1-21"},"PeriodicalIF":3.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144566098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Adaptive Selection for False Discovery Rate Control Leveraging Symmetry 利用对称性控制错误发现率的自适应选择
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2025-07-03 DOI: 10.1080/01621459.2025.2519814
Kehan Wang, Yuexin Chen, Yixin Han, Wangli Xu, Linglong Kong
{"title":"Adaptive Selection for False Discovery Rate Control Leveraging Symmetry","authors":"Kehan Wang, Yuexin Chen, Yixin Han, Wangli Xu, Linglong Kong","doi":"10.1080/01621459.2025.2519814","DOIUrl":"https://doi.org/10.1080/01621459.2025.2519814","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"629 1","pages":"1-21"},"PeriodicalIF":3.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Checking the Cox Proportional Hazards Model with Interval-Censored Data 用区间截尾数据检验Cox比例风险模型
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2025-07-03 DOI: 10.1080/01621459.2025.2520460
Yangjianchen Xu, Donglin Zeng, D. Y. Lin
{"title":"Checking the Cox Proportional Hazards Model with Interval-Censored Data","authors":"Yangjianchen Xu, Donglin Zeng, D. Y. Lin","doi":"10.1080/01621459.2025.2520460","DOIUrl":"https://doi.org/10.1080/01621459.2025.2520460","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"7 1","pages":"1-21"},"PeriodicalIF":3.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
On a Notion of Graph Centrality Based on L1 Data Depth 基于L1数据深度的图中心性概念
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2025-07-03 DOI: 10.1080/01621459.2025.2520467
Seungwoo Kang, Hee-Seok Oh
{"title":"On a Notion of Graph Centrality Based on L1 Data Depth","authors":"Seungwoo Kang, Hee-Seok Oh","doi":"10.1080/01621459.2025.2520467","DOIUrl":"https://doi.org/10.1080/01621459.2025.2520467","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"46 1","pages":"1-22"},"PeriodicalIF":3.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Kernel density estimation with polyspherical data and its applications 多球面数据核密度估计及其应用
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2025-07-03 DOI: 10.1080/01621459.2025.2521898
Eduardo García-Portugués, Andrea Meilán-Vila
{"title":"Kernel density estimation with polyspherical data and its applications","authors":"Eduardo García-Portugués, Andrea Meilán-Vila","doi":"10.1080/01621459.2025.2521898","DOIUrl":"https://doi.org/10.1080/01621459.2025.2521898","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"1 1","pages":"1-25"},"PeriodicalIF":3.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Higher-order accurate two-sample network inference and network hashing 高阶精确双样本网络推理和网络哈希
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2025-07-03 DOI: 10.1080/01621459.2025.2520459
Meijia Shao, Dong Xia, Yuan Zhang, Qiong Wu, Shuo Chen
{"title":"Higher-order accurate two-sample network inference and network hashing","authors":"Meijia Shao, Dong Xia, Yuan Zhang, Qiong Wu, Shuo Chen","doi":"10.1080/01621459.2025.2520459","DOIUrl":"https://doi.org/10.1080/01621459.2025.2520459","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"79 1","pages":"1-26"},"PeriodicalIF":3.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144566037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Data-Driven Tuning Parameter Selection for High-Dimensional Vector Autoregressions 数据驱动的高维矢量自回归调优参数选择
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2025-06-27 DOI: 10.1080/01621459.2025.2516190
Anders B. Kock, Rasmus S. Pedersen, Jesper R.-V. Sørensen
{"title":"Data-Driven Tuning Parameter Selection for High-Dimensional Vector Autoregressions","authors":"Anders B. Kock, Rasmus S. Pedersen, Jesper R.-V. Sørensen","doi":"10.1080/01621459.2025.2516190","DOIUrl":"https://doi.org/10.1080/01621459.2025.2516190","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"630 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144500393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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