A study of longitudinal trends in time-frequency transformations of EEG data during a learning experiment [0.03%]
基于学习实验过程中EEG数据时间频率变换的纵向研究趋势
Joanna Boland,Donatello Telesca,Catherine Sugar et al.
Joanna Boland et al.
EEG experiments yield high-dimensional event-related potential (ERP) data in response to repeatedly presented stimuli throughout the experiment. Changes in the high-dimensional ERP signal throughout the duration of an experiment (longitudin...
Joint Estimation of Monotone Curves via Functional Principal Component Analysis [0.03%]
基于函数主成分分析的单调曲线联合估计
Yei Eun Shin,Lan Zhou,Yu Ding
Yei Eun Shin
A functional data approach is developed to jointly estimate a collection of monotone curves that are irregularly and possibly sparsely observed with noise. In this approach, the unconstrained relative curvature curves instead of the monoton...
Statistical Inference for High-Dimensional Pathway Analysis with Multiple Responses [0.03%]
高维通路分析多重响应的统计推断
Yang Liu,Wei Sun,Li Hsu et al.
Yang Liu et al.
Pathway analysis, i.e., grouping analysis, has important applications in genomic studies. Existing pathway analysis approaches are mostly focused on a single response and are not suitable for analyzing complex diseases that are often relate...
Seongho Kim,Weng Kee Wong
Seongho Kim
A common endpoint in a single-arm phase II study is tumor response as a binary variable. Two widely used designs for such a study are Simon's two-stage minimax and optimal designs. The minimax design minimizes the maximal sample size and th...
Missing link survival analysis with applications to available pandemic data [0.03%]
缺失链生存分析及其在流感大流行数据中的应用
María Luz Gámiz,Enno Mammen,María Dolores Martínez-Miranda et al.
María Luz Gámiz et al.
It is shown how to overcome a new missing data problem in survival analysis. Iterative nonparametric techniques are utilized and the missing data information is both estimated and used for further estimation in each iterative step. Theory i...
Conditional Independence Test of Failure and Truncation Times: Essential Tool for Method Selection [0.03%]
失效时间和截尾时间的条件独立性检验——方法选择的重要工具
Jing Ning,Daewoo Pak,Hong Zhu et al.
Jing Ning et al.
Conditional independence assumption of truncation and failure times conditioning on covariates is a fundamental and common assumption in the regression analysis of left-truncated and right-censored data. Testing for this assumption is essen...
Weijuan Liang,Shuangge Ma,Cunjie Lin
Weijuan Liang
Survival analysis that involves moderate/high dimensional covariates has become common. Most of the existing analyses have been focused on estimation and variable selection, using penalization and other regularization techniques. To draw mo...
Response adaptive designs for Phase II trials with binary endpoint based on context-dependent information measures [0.03%]
基于上下文依赖信息度量的二值终点二期临床试验自适应设计方法研究
Ksenia Kasianova,Mark Kelbert,Pavel Mozgunov
Ksenia Kasianova
In many rare disease Phase II clinical trials, two objectives are of interest to an investigator: maximising the statistical power and maximising the number of patients responding to the treatment. These two objectives are competing, theref...
Optimal treatment regimes for competing risk data using doubly robust outcome weighted learning with bi-level variable selection [0.03%]
基于双稳健结果加权学习和双水平变量选择的竞风险数据最优处理方案研究
Yizeng He,Soyoung Kim,Mi-Ok Kim et al.
Yizeng He et al.
The goal of the optimal treatment regime is maximizing treatment benefits via personalized treatment assignments based on the observed patient and treatment characteristics. Parametric regression-based outcome learning approaches require ex...
Generalized [Formula: see text] -means in GLMs with applications to the outbreak of COVID-19 in the United States [0.03%]
美国新冠疫情下的广义线性模型中的广义[Formula: see text] -均值及其应用
Tonglin Zhang,Ge Lin
Tonglin Zhang
Generalized k -means can be combined with any similarity or dissimilarity measure for clustering. Using the well known likelihood ratio or F -statistic as the dissimilarity measure, a generalized k -means method is proposed to group general...