Hazards Constitute Key Quantities for Analyzing, Interpreting and Understanding Time-to-Event Data [0.03%]
风险构成分析、解读和理解生存数据的关键指标
Jan Beyersmann,Claudia Schmoor,Martin Schumacher
Jan Beyersmann
Censoring makes time-to-event data special and requires customized statistical techniques. Survival and event history analysis therefore builds on hazards as the identifiable quantities in the presence of rather general censoring schemes. T...
Estimating the Optimal Time to Perform a Positron Emission Tomography With Prostate-Specific Membrane Antigen in Prostatectomized Patients, Based on Data From Clinical Practice [0.03%]
基于临床实践数据估计前列腺切除患者进行前列腺特异性膜抗原正电子发射断层扫描的 optimal 时间
Martina Amongero,Gianluca Mastrantonio,Stefano De Luca et al.
Martina Amongero et al.
Prostatectomized patients are at risk of resurgence, and for this reason, during a follow-up period, they are monitored for prostate-specific antigen (PSA) growth, an indicator of tumor progression. The presence of tumors can be evaluated w...
Semi-Markov Multistate Modeling Approaches for Multicohort Event History Data [0.03%]
多重队列事件史数据的半马科夫多状态模型方法研究
Xavier Piulachs,Klaus Langohr,Mireia Besalú et al.
Xavier Piulachs et al.
Two Cox-based multistate modeling approaches are compared for modeling a complex multicohort event history process. The first approach incorporates cohort information as a fixed covariate, thereby providing a direct estimation of the cohort...
How Should Parallel Cluster Randomized Trials With a Baseline Period be Analyzed?-A Survey of Estimands and Common Estimators [0.03%]
平行区组随机临床试验中如何分析基线期的作用？——估计量与参数调查分析
Kenneth Menglin Lee,Fan Li
Kenneth Menglin Lee
The parallel cluster randomized trial with baseline (PB-CRT) is a common variant of the standard parallel cluster randomized trial (P-CRT). We define two natural estimands in the context of PB-CRTs with informative cluster sizes, the indivi...
Elena Sabbioni,Claudio Agostinelli,Alessio Farcomeni
Elena Sabbioni
We propose a MANOVA test for semicontinuous data that is applicable also when the dimension exceeds the sample size. The test statistic is obtained as a likelihood ratio, where the numerator and denominator are computed at the maxima of pen...
Bayesian Inference of Phenotypic Plasticity of Cancer Cells Based on Dynamic Model for Temporal Cell Proportion Data [0.03%]
基于时间依赖细胞比例数据的癌症细胞表型可塑性的动态模型及其贝叶斯推断
Shuli Chen,Yuman Wang,Da Zhou et al.
Shuli Chen et al.
Mounting evidence underscores the prevalent hierarchical organization of cancer tissues. At the foundation of this hierarchy reside cancer stem cells, a subset of cells endowed with the pivotal role of engendering the entire cancer tissue t...
Impact of Methodological Assumptions and Covariates on the Cutoff Estimation in ROC Analysis [0.03%]
方法假设和协变量对ROC分析中截止值估计的影响
Soutik Ghosal
Soutik Ghosal
The receiver operating characteristic (ROC) curve stands as a cornerstone in assessing the efficacy of biomarkers for disease diagnosis. Beyond merely evaluating performance, it provides with an optimal cutoff for biomarker values, crucial ...
Werner Brannath,Thorsten Dickhaus,Ruth Heller et al.
Werner Brannath et al.
On Sample Size Determination for Augmented Tests Based on Restricted Mean Survival Time in Randomized Clinical Trials [0.03%]
随机临床试验中基于受限平均生存时间的扩充检验样本量确定方法研究
Satoshi Hattori,Hajime Uno
Satoshi Hattori
Restricted mean survival time (RMST) is gaining attention as a measure to quantify the treatment effect on survival outcomes in randomized clinical trials. Several methods to determine sample size based on the RMST-based tests have been pro...
The Shared Weighted Lindley Frailty Model for Clustered Failure Time Data [0.03%]
用于分析聚类失效时间数据的共享加权Lindley frailty模型
Diego I Gallardo,Marcelo Bourguignon,John L Santibáñez
Diego I Gallardo
The primary goal of this paper is to introduce a novel frailty model based on the weighted Lindley (WL) distribution for modeling clustered survival data. We study the statistical properties of the proposed model. In particular, the amount ...