A Comparison of Methods for Treatment Selection in Seamless Phase II/III Design [0.03%]
适应无缝二期/三期临床试验设计的治疗选择方法比较研究
Jialuo Liu,Lulu Wang,Dong Xi
Jialuo Liu
Seamless phase II/III design aims to integrate a phase II trial for treatment selection and a phase III confirmatory trial. It offers valuable flexibility through mid-trial modifications, potentially optimizing resource utilization and redu...
Comparative Study
Biometrical journal. Biometrische Zeitschrift. 2026 Jun;68(3):e70136. DOI:10.1002/bimj.70136 2026
Causal Effect Estimation With TMLE: Handling Missing Data and Near Violations of Positivity [0.03%]
利用TMLE估计因果效应：处理缺失数据和接近 positivity 违背的情况
Christoph Wiederkehr,Christian Heumann,Michael Schomaker
Christoph Wiederkehr
We evaluate the performance of targeted maximum likelihood estimation (TMLE) for estimating the average treatment effect in missing data scenarios under varying levels of positivity violations. We employ model- and design-based simulations,...
Identifying the Best Predictive Biomarker in Pharmacogenomics Through Multiple Comparisons With the Best [0.03%]
通过最佳比较法在药物基因组学中识别最佳预测生物标志物
Song Zhai,Judong Shen,Jason C Hsu et al.
Song Zhai et al.
Single gene mutations are increasingly being adopted as clinical biomarkers for the optimal application of various therapeutic areas (such as cancer and cardiovascular disease). A single nucleotide polymorphism (SNP), the most common type o...
Comparative Study
Biometrical journal. Biometrische Zeitschrift. 2026 Apr;68(2):e70130. DOI:10.1002/bimj.70130 2026
Estimating the Size of a Population Through Repeated Sampling: A Survey Sampling View on Capture-Recapture Procedures [0.03%]
重复抽样估计总体规模：一种关于捕捉-标记-重捕程序的调查抽样观点
Nurzhan Sapargali,Göran Kauermann
Nurzhan Sapargali
Capture-recapture methods estimate the size of an elusive population based on repeated partial observations. In closed populations, estimators are typically constructed by modeling either the probability of capture frequencies or entire cap...
Estimate Time-Varying Exposure Effects via Ensemble Learning-Based Marginal Structural Model With Application to Adolescent Cognitive Development Study [0.03%]
基于集成学习的边际结构模型的时变暴露效应估计及其在青少年认知发展研究中的应用
Zhiwei Zhao,Chixiang Chen,Shuo Chen
Zhiwei Zhao
Evaluating the effects of time-varying exposures is essential for longitudinal studies. The effect estimation becomes increasingly challenging when dealing with hundreds of time-dependent confounders. We propose a Marginal Structure Ensembl...
Regression Analysis of Arbitrarily Censored and Left-Truncated Data Under the Proportional Odds Model [0.03%]
比例优势回归分析及其在左截尾数据下的删失数据分析
Lu Wang,Lianming Wang
Lu Wang
In survival analysis, the exact times of an event of interest may not always be observed due to the nature of the event and the study design for all subjects but are usually partially observed subject to censoring and truncation in many rea...
Inferring on Joint Associations From Marginal Associations and a Reference Sample [0.03%]
边际关联和参考样本中的联合关联推理
Tzviel Frostig,Ruth Heller
Tzviel Frostig
We present a method to infer on joint regression coefficients obtained from marginal regressions using a reference panel. This type of scenario is common in genetic fine-mapping, where the estimated marginal associations are reported in gen...
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,...