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作者：Morris, Emily L.; He, Kevin; Kang, Jian
作者单位：University of Michigan System; University of Michigan
摘要：Neuroimaging studies have a growing interest in learning the association between the individual brain connectivity networks and their clinical char-acteristics. It is also of great interest to identify the sub-brain networks as biomarkers to predict the clinical symptoms, such as disease status, poten-tially providing insight on neuropathology. This motivates the need for devel-oping a new type of regression model where the response variable is scalar, and predictors are networks that are typi...
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作者：Embleton, Jonathan; Knight, Marina I.; Ombao, Hernando
作者单位：University of York - UK; King Abdullah University of Science & Technology
摘要：Within the neurosciences it is natural to observe variability across time in the dynamics of an underlying brain process. Wavelets are essential in analysing brain signals because, even within a single trial, brain signals exhibit nonstationary behaviour. However, neurological signals generated within an experiment may also potentially exhibit evolution across trials (replicates), even for identical stimuli. As neurologists consider localised spectra of brain signals to be most informative, we...
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作者：Hu, Zonghui; Zhang, Zhiwei; Follmann, Dean
作者单位：National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID); National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI)
摘要：A randomized trial is the gold standard for assessing the benefit of a treat-ment versus a control. When noncompliance is present, treatment effect de-pends on the tendency to comply-an attribute that is not directly measurable. Though the principal causal effect has been the most important for handling noncompliance, it is not immediately applicable to clinical decision-making as it targets the average effect in the latent strata of potential compliance. In this work, we propose the concept o...
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作者：Feldman, Joseph; Kowal, Daniel R.
作者单位：Rice University
摘要：Much of the microdata used for epidemiological studies contain sensi-tive measurements on real individuals. As a result, such microdata cannot be published out of privacy concerns, and without public access to these data, any statistical analyses originally published on them are nearly impos-sible to reproduce. To promote the dissemination of key datasets for analy-sis without jeopardizing the privacy of individuals, we introduce a cohesive Bayesian framework for the generation of fully synthe...
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作者：Zhang, Weiz; Zhang, Zhi wei; Troendle, James F.; Liu, Aiyi
作者单位：Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); National Institutes of Health (NIH) - USA; NIH National Heart Lung & Blood Institute (NHLBI); National Institutes of Health (NIH) - USA; NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
摘要：Predictive and prognostic biomarkers are increasingly important in clini-cal research and practice. Biomarker studies are frequently embedded in ran-domized clinical trials with biospecimens collected at baseline and assayed for biomarkers, either in real time or retrospectively. This article proposes efficient estimation strategies for two study settings in terms of biomarker ascertainment: a complete-data setting in which the biomarker is measured for all subjects in the trial, and a two-pha...
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作者：Richards, Jordan; Tawn, Jonathan A.; Brown, Simon
作者单位：Lancaster University; Met Office - UK; Hadley Centre
摘要：Inference on the extremal behaviour of spatial aggregates of precipitation is important for quantifying river flood risk. There are two classes of previous approach, with one failing to ensure self-consistency in inference across different regions of aggregation and the other imposing highly restrictive assumptions. To overcome these issues, we propose a model for high-resolution precipitation data from which we can simulate realistic fields and explore the behaviour of spatial aggregates. Rec...
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作者：Wang, Zhengfan; Fix, Miranda J.; Hug, Lucia; Mishra, Anu; You, Danzhen; Blencowe, Hannah; Wakefield, Jon; Alkema, Leontine
作者单位：University of Massachusetts System; University of Massachusetts Amherst; University of Washington; University of Washington Seattle; UNICEF; University of London; London School of Hygiene & Tropical Medicine
摘要：Estimation of stillbirth rates globally is complicated because of the paucity of reliable data from countries where most stillbirths occur. We com-piled data and developed a Bayesian hierarchical temporal sparse regression model for estimating stillbirth rates for 195 countries from 2000 to 2019. The model combines covariates with a temporal smoothing process so that estimates are data-driven in country-periods with high-quality data and deter-mined by covariates for country-periods with limit...
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作者：Zhao, Sen; Ali, Shojaie
作者单位：Alphabet Inc.; Google Incorporated; University of Washington; University of Washington Seattle
摘要：Identifying differences in networks has become a canonical problem in many biological applications. Existing methods try to accomplish this goal by either directly comparing the estimated structures of two networks or test-ing the null hypothesis that the covariance or inverse covariance matrices in two populations are identical. However, estimation approaches do not pro-vide measures of uncertainty, for example, p-values, whereas existing testing approaches could lead to misleading results, a...
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作者：Sung, Chih-Li
作者单位：Michigan State University
摘要：As the coronavirus disease 2019 (COVID-19) has shown profound ef-fects on public health and the economy worldwide, it becomes crucial to as-sess the impact on the virus transmission and develop effective strategies to address the challenge. A new statistical model, derived from the SIR epidemic model with functional parameters, is proposed to understand the impact of weather and government interventions on the virus spread in the presence of asymptomatic infections among eight metropolitan are...
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作者：Lin, Ruitao; Shi, Haolun; Yin, Guosheng; Thali, Peter F.; Yuan, Ying; Flowers, Christopher R.
作者单位：University of Texas System; UTMD Anderson Cancer Center; Simon Fraser University; University of Hong Kong; University of Texas System; UTMD Anderson Cancer Center
摘要：We propose a curve-free random-effects meta-analysis approach to combining data from multiple phase I clinical trials to identify an optimal dose. Our method accounts for between-study heterogeneity that may stem from different study designs, patient populations, or tumor types. We also develop a meta-analytic-predictive (MAP) method, based on a power prior, that incorporates data from multiple historical studies into the design and conduct of a new phase I trial. Performances of the proposed ...
