Enhancing Team Science by Training Collaborative Biostatisticians to have a Strong Statistical Voice [0.03%]
通过培训具有强大统计声音的合作生物统计学家来增强团队科学能力
Gina-Maria Pomann,Steven C Grambow,Marissa C Ashner et al.
Gina-Maria Pomann et al.
Strong statistical voice is defined as the ability to advocate and negotiate for good and ethical statistical practices, including integrating and resolving differing scientific approaches. This skill is crucial for biostatisticians who wor...
A Statistical Analysis Plan Template for Observational Studies: Promoting Quality and Rigor in Research [0.03%]
观察性研究的统计分析计划模板：促进研究的质量和严谨性
Hunna J Watson
Hunna J Watson
Rigorous and transparent research practices are essential for trustworthy scientific findings, particularly in observational studies where data-driven analyses carry risks of questionable research practices. This paper introduces a statisti...
More than presence-absence; modelling (e)DNA concentration across time and space from qPCR survey data [0.03%]
浓度先行：时空视角下的(e)DNA浓度模型构建及其qPCR调查数据应用
Milly Jones,Eleni Matechou,Diana Cole et al.
Milly Jones et al.
Environmental DNA (eDNA) surveys offer a revolutionary approach to species monitoring by detecting DNA traces left by organisms in environmental samples, such as water and soil. These surveys provide a cost-effective, non-invasive, and high...
A Weighted Survival Regression Framework for Incorporating External Prediction Information [0.03%]
一种新的加权生存回归框架：利用外部预测信息提高生存分析性能
Debashis Ghosh
Debashis Ghosh
In this article, we develop a weighted approach to estimation for right-censored time to event data in the presence of external predictions available from a prediction model. There are several advantages to the proposed approach. First, the...
Frank Röttger,Thomas Kahle,Rainer Schwabe
Frank Röttger
In discrete choice experiments, the information matrix depends on the model parameters. Therefore designing optimally informative experiments for arbitrary initial parameters often yields highly nonlinear optimization problems and makes opt...
Applications of Deep Neural Networks with Fractal Structure and Attention Blocks for 2D and 3D Brain Tumor Segmentation [0.03%]
具有分形结构和注意模块的深度神经网络在2D和3D脑肿瘤分割中的应用
Kaiming Cheng,Yueyang Shen,Ivo D Dinov
Kaiming Cheng
In this paper, we propose a novel deep neural network (DNN) architecture with fractal structure and attention blocks. The new method is tested to identify and segment 2D and 3D brain tumor masks in normal and pathological neuroimaging data....
Myron Katzoff,Wen Zhou,Diba Khan et al.
Myron Katzoff et al.
The probability that mortality from certain causes exceeds high thresholds is addressed. An out-of-sample fusion method is presented where an original real data sample is fused or combined with independent computer-generated samples in the ...
Mei Ling Huang,Yansan Han,William Marshall
Mei Ling Huang
Extreme events, such as earthquakes, tsunamis, and market crashes, can have substantial impact on social and ecological systems. Quantile regression can be used for predicting these extreme events, making it an important problem that has ap...
Eda Gizem Koçyiğit,Khalid Ul Islam Rather
Eda Gizem Koçyiğit
In this study, a new sub-regression type estimator for ranked set sampling (RSS) is proposed based on the idea of a sub-ratio estimator given in Koçyiğit and Kadılar (Commun Stat Theory Methods 1-23, 2022). The proposed unbiased estimato...
Bayesian Analysis of First-Order Markov Models for Autocorrelated Binary Responses [0.03%]
用于自相关二元反应的第一阶马尔科夫模型的贝叶斯分析
Dasom Lee,Sujit Ghosh
Dasom Lee
In many clinical trials, patient outcomes are often binary-valued which are measured asynchronously over time across various dose levels. To account for autocorrelation among such longitudinally observed outcomes, a first-order Markov model...