An omnibus approach to assess covariate balance in observational studies using the distance covariance [0.03%]
一种基于距离协方差的评估观察性研究中协变量平衡的全面方法
Adin-Cristian Andrei,Patrick M McCarthy
Adin-Cristian Andrei
Adequate baseline covariate balance among groups is critical in observational studies designed to estimate causal effects. Propensity score-based methods are popular ways to achieve covariate balance among groups. Existing methods are not e...
Cluster-specific nonignorably missing, endogenous, and continuous regressors in multilevel model for binary outcome [0.03%]
多层模型中聚类特定的非忽略连续内生协变量及二分类结果变量中的应用
Gi-Soo Kim,Youngjo Lee,Hongsoo Kim et al.
Gi-Soo Kim et al.
In multilevel regression models for observational clustered data, regressors can be correlated with cluster-level error components, namely endogenous, due to omitted cluster-level covariates, measurement error, and simultaneity. When endoge...
Hyunkeun Ryan Cho,Seonjin Kim,Myung Hee Lee
Hyunkeun Ryan Cho
Biomedical studies often involve an event that occurs to individuals at different times and has a significant influence on individual trajectories of response variables over time. We propose a statistical model to capture the mean trajector...
Saswati Saha,Werner Brannath,Björn Bornkamp
Saswati Saha
Drug combination trials are often motivated by the fact that individual drugs target the same disease but via different routes. A combination of such drugs may then have an overall better effect than the individual treatments which has to b...
Quantile contours and allometric modelling for risk classification of abnormal ratios with an application to asymmetric growth-restriction in preterm infants [0.03%]
分位数轮廓及量纲建模在异常比率风险分类中的应用——以早产儿生长不对称受限为例
Marco Geraci,Nansi S Boghossian,Alessio Farcomeni et al.
Marco Geraci et al.
We develop an approach to risk classification based on quantile contours and allometric modelling of multivariate anthropometric measurements. We propose the definition of allometric direction tangent to the directional quantile envelope, w...
Simultaneous inference for multiple marginal generalized estimating equation models [0.03%]
多个边际广义估计方程模型的联合推断
Robin Ristl,Ludwig Hothorn,Christian Ritz et al.
Robin Ristl et al.
Motivated by small-sample studies in ophthalmology and dermatology, we study the problem of simultaneous inference for multiple endpoints in the presence of repeated observations. We propose a framework in which a generalized estimating equ...
Yujing Xie,Zangdong He,Wanzhu Tu et al.
Yujing Xie et al.
Many clinical studies collect longitudinal and survival data concurrently. Joint models combining these two types of outcomes through shared random effects are frequently used in practical data analysis. The standard joint models assume tha...
Corrigendum [0.03%]
勘误表
Evaluation of multiple prediction models: A novel view on model selection and performance assessment [0.03%]
多预测模型评估：模型选择和性能评估的新视角
Max Westphal,Werner Brannath
Max Westphal
Model selection and performance assessment for prediction models are important tasks in machine learning, e.g. for the development of medical diagnosis or prognosis rules based on complex data. A common approach is to select the best model ...
Flexible Bayesian excess hazard models using low-rank thin plate splines [0.03%]
用于低秩薄板样条的灵活贝叶斯超额危险度模型
Manuela Quaresma,James Carpenter,Bernard Rachet
Manuela Quaresma
Excess hazard models became the preferred modelling tool in population-based cancer survival research. In this setting, the model is commonly formulated as the additive decomposition of the overall hazard into two components: the excess haz...