The Poisson CUSUM Chart for Monitoring Small Counts: Addressing the Estimation Uncertainty [0.03%]
泊松CUM图的小计数监测：解决估计不确定性问题
Stan Heidema,Ivo V Stoepker,Ralph Huits et al.
Stan Heidema et al.
This study addresses the impact of estimating in-control parameters on the performance of the Poisson cumulative sum (CUSUM) chart in detecting an increase in the mean when the counts are small. To reduce false signals induced by estimation...
Joint Model for Interval-Censored Semicompeting Events and Longitudinal Data With Subject-Specific Within- and Between-Visits Variabilities [0.03%]
考虑纵向数据中访视内和访视间变异的联合模型
Léonie Courcoul,Catherine Helmer,Antoine Barbieri et al.
Léonie Courcoul et al.
Dementia currently affects about 50 million people worldwide, and this number is rising. Since there is still no cure, the primary focus remains on preventing modifiable risk factors such as cardiovascular factors. It is now recognized that...
Bayesian Integrative Detection of Structural Variations With False Discovery Rate Control [0.03%]
控制错误发现率的贝叶斯整合检测结构变异方法
Sheng Lian,Jiandong Shi,Jingyu Hao et al.
Sheng Lian et al.
Recent advances in long-read sequencing technologies have empowered the detection of structural variations (SVs) associated with genetic diseases. Despite the availability of numerous SV callers and efforts to merge SVs from multiple tools,...
Contrasting Global and Patient-Specific Regression Models via a Neural Network Representation [0.03%]
基于神经网络表示的全局和患者特定回归模型的比较
Max Behrens,Daiana Stolz,Eleni Papakonstantinou et al.
Max Behrens et al.
When developing clinical prediction models, it can be challenging to balance between global models that are valid for all patients and personalized models tailored to individuals or potentially unknown subgroups. To aid such decisions, we p...
Reducing the Effect of Correlated Additive Measurement Errors on Regression Model With no Ancillary Study [0.03%]
降低相关性加性测量误差对无辅助研究回归模型的影响
Zhiqiang Cao,Man Yu Wong
Zhiqiang Cao
To adjust the effect of additive measurement error on estimation and hypothesis testing, one needs some information on the measurement error model, that is, an ancillary study (e.g., validation study, calibration study, or replicates study)...
Extending t linear mixed models for longitudinal data with non-ignorable dropout applied to AIDS studies [0.03%]
具有不可忽略缺失的纵向数据的t混合效应模型及其在艾滋病研究中的应用
Yu-Chen Yang,Wan-Lun Wang,Luis M Castro et al.
Yu-Chen Yang et al.
One typical missing pattern in longitudinal data is dropout in the sense that some participants may withdraw prematurely and never return. Dropout is generally regarded as a non-ignorable mechanism when the probability of the occurrence of ...
A Novel Approach to the Design and Sample Size Planning of Animal Experiments Based on Effect Estimation [0.03%]
基于效应估计的动物实验设计和样本量规划的新方法
Dario Zocholl,Henrike Solveen,Matthias Schmid
Dario Zocholl
Animal experiments are often purely exploratory, with little to no data available to support the planning phase. Nonetheless, ethical guidelines demand scientifically sound planning, particularly regarding sample size determination based on...
Impact of Treatment Effect Heterogeneity on the Estimation of Individualized Treatment Rules for Count Outcomes [0.03%]
处理效应异质性对计数结果个体化治疗决策的影响研究
Xiaotong Jiang,Gabrielle Simoneau,Bora Youn et al.
Xiaotong Jiang et al.
There is growing interest in tailoring treatment decisions to individual patient characteristics, but few studies have examined the implementation and performance of individualized treatment rules (ITRs) for count data. Our objective was to...
Tsz Pang Yuen,Eni Musta
Tsz Pang Yuen
In order to estimate the proportion of "immune" or "cured" subjects who will never experience failure, a sufficiently long follow-up period is required. Several statistical tests have been proposed in the literature for assessing the assump...
Bivariate Quantile Residual Life Functions for Estimating Immunological and Virological Recovery in HIV Patients [0.03%]
HIV患者免疫学和病毒学恢复的双变量分位数残差寿命函数估计
Ruhul Ali Khan,Musie Ghebremichael
Ruhul Ali Khan
Monitoring both immunological and virological outcome measures provides the most accurate and meaningful assessment of the human immunodeficiency virus (HIV) treatment effectiveness. However, evaluating treatment efficacy based solely on ei...