Discrimination performance in illness-death models with interval-censored disease data [0.03%]
区间截断疾病数据下的病死模型的判别性能分析
Marta Spreafico,Anja J Rueten-Budde,Hein Putter et al.
Marta Spreafico et al.
In clinical studies, the illness-death model is often used to describe disease progression. A subject starts disease-free, may develop the disease and then die, or die directly. In clinical practice, disease can only be diagnosed at pre-spe...
Parametric and nonparametric propensity score weighting analysis with subgroup covariate balance [0.03%]
具有亚组协变量平衡的参数和非参数倾向性评分加权分析
Yan Li,Yong-Fang Kuo,Liang Li
Yan Li
Estimating the causal treatment effects by subgroups is important in observational studies when the treatment effect heterogeneity is present. Existing propensity score methods rely on a correctly specified propensity score model. Model mis...
A historical note: Rediscovering an unpublished response to Korn and Freidlin (2011) [0.03%]
历史注记：重新发现对Korn和Freidlin(2011)的未发表答复
Hongjian Zhu,William F Rosenberger,Feifang Hu et al.
Hongjian Zhu et al.
Despite extensive research, the use of response-adaptive randomization (RAR) in clinical trials has remained controversial. Korn and Freidlin's 2011 article reignited this debate back then, prompting numerous responses, including one by Zhu...
Truncated Gaussian copula principal component analysis with application to pediatric acute lymphoblastic leukemia patients' gut microbiome [0.03%]
具有应用价值的截断高斯库恩卡主成分分析：以儿科急性淋巴细胞白血病患者的肠道微生物组为例
Lei Wang,Yang Ni,Irina Gaynanova
Lei Wang
Increasing epidemiologic evidence suggests that the diversity and composition of the gut microbiome can predict infection risk in cancer patients. Infections remain a major cause of morbidity and mortality during chemotherapy. Analyzing mic...
A fast integrative clustering and feature selection approach for high-dimensional multiview data [0.03%]
一种高效整合聚类和特征选择的高维多视图数据处理方法
Abdalkarim Alnajjar,Helen Bian,Zihang Lu
Abdalkarim Alnajjar
Cluster analysis has been widely used in biomedical studies for disaggregating heterogeneous diseases and identifying disease subtypes that may inform clinical decisions. In the era of advanced data science and engineering, cluster analysis...
Cluster analysis for longitudinal data and its application in the detection of adiposity trajectories [0.03%]
纵向数据分析及其在肥胖症发展路径检测中的应用
Asael Fabian Martínez,Ivonne Ramírez-Silva,Ruth Fuentes-García
Asael Fabian Martínez
The identification of latent profile trajectories in longitudinal studies represents an important challenge for specialists since they could provide insights to better understand their problem of interest. The majority of the statistical me...
A permutation test of differences between externally or internally defined groupings in compositional data sets [0.03%]
compositional数据集中外部或内部定义的组别差异的置换检验
Nikola Štefelová,Javier Palarea-Albaladejo,Josep Antoni Martín-Fernández
Nikola Štefelová
Testing group differences in compositional data, that is, multivariate data referring to parts of a whole, requires focussing on the relative information between components. This is commonly achieved by mapping the data into a sensible logr...
Dynamic prediction of interval-censored failure time data with longitudinal marker [0.03%]
纵向标志物的区间删失失效时间数据的动态预测
Yang-Jin Kim
Yang-Jin Kim
A main interest in clinical practice is the prediction of patient prognosis conductive to decision making. Therefore, a relevant prediction model should be able to reflect the updated patient's condition. A joint model of longitudinal marke...
Hazard-based distributional regression via ordinary differential equations [0.03%]
基于危险率的分布回归的常微分方程方法
Jose A Christen,Francisco J Rubio
Jose A Christen
The hazard function is central to the formulation of commonly used survival regression models such as the proportional hazards and accelerated failure time models. However, these models rely on a shared baseline hazard, which, when specifie...
A burn-in(g) question: How long should an initial equal randomization stage be before Bayesian response-adaptive randomization? [0.03%]
一个关于烧录的问题：在贝叶斯自适应随机化之前，初始均衡随机化的阶段应该持续多久？
Edwin Yn Tang,Stef Baas,Daniel Kaddaj et al.
Edwin Yn Tang et al.
Response-adaptive randomization (RAR) can increase participant benefit in clinical trials, but also complicates statistical analysis. The burn-in period-a non-adaptive initial stage-is commonly used to mitigate this disadvantage, yet guidan...