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期刊名:Journal of the american statistical association

缩写:J AM STAT ASSOC

ISSN:0162-1459

e-ISSN:1537-274X

IF/分区:3.0/Q1

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Clinical Trial Case Reports Meta-Analysis RCT Review Systematic Review
Classical Article Case Reports Clinical Study Clinical Trial Clinical Trial Protocol Comment Comparative Study Editorial Guideline Letter Meta-Analysis Multicenter Study Observational Study Randomized Controlled Trial Review Systematic Review
Ling Ma,Rajeshwari Sundaram Ling Ma
In biomedical studies, one is often interested in repeat events with longitudinal observations occurring only intermittently, resulting in panel count data. The first stage of labor, measured through unit-increments of cervical dilation in ...
Chixiang Chen,Shuo Chen,Zhenyao Ye et al. Chixiang Chen et al.
Although substance use, such as alcohol intake, is known to be associated with cognitive decline during aging, its direct influence on the central nervous system remains incompletely understood. In this study, we investigate the influence o...
Huijuan Ma,Wei Zhao,John Hanfelt et al. Huijuan Ma et al.
Chronic disease studies often collect data on biological and clinical markers at follow-up visits to monitor disease progression. Viewing such longitudinal measurements governed by latent continuous trajectories, we develop a new dynamic re...
Sami Leon,Tong Tong Wu Sami Leon
In longitudinal research, it is essential to compare sets of trajectories, commonly seen as changes over time in different treatment or patient groups. This paper presents a partial linear semiparametric mixed-effects model (PLSMM) for the ...
Lu Zhang,Wenpin Tang,Sudipto Banerjee Lu Zhang
We develop Bayesian predictive stacking for geostatistical models, where the primary inferential objective is to provide inference on the latent spatial random field and conduct spatial predictions at arbitrary locations. We exploit analyti...
Yubai Yuan,Yijiao Zhang,Babak Shahbaba et al. Yubai Yuan et al.
Detecting dynamic patterns shared across heterogeneous datasets is a critical yet challenging task in many scientific domains, particularly within the biomedical sciences. Systematic heterogeneity inherent in diverse data sources can signif...
Lorenzo Cappello,Amandine Véber,Julia A Palacios Lorenzo Cappello
Molecular sequence variation at a locus informs about the evolutionary history of the sample and past population size dynamics. The Kingman coalescent is used in a generative model of molecular sequence variation to infer evolutionary param...
Jin-Hong Du,Zhenghao Zeng,Edward H Kennedy et al. Jin-Hong Du et al.
With the evolution of single-cell RNA sequencing techniques into a standard approach in genomics, it has become possible to conduct cohort-level causal inferences based on single-cell-level measurements. However, the individual gene express...
Yibo Wang,Sunghee Lee,Michael R Elliott Yibo Wang
Respondent-driven sampling (RDS) is widely used to collect data from hidden populations in social and biomedical science. Although RDS may provide comprehensive coverage of the target hidden population through social network recruitment, it...
Sijia Li,Peter B Gilbert,Rui Duan et al. Sijia Li et al.
We introduce a new data fusion method that utilizes multiple data sources to estimate a smooth, finite-dimensional parameter. Most existing methods only make use of fully aligned data sources that share common conditional distributions of o...