Author correction to: "causal survival analysis under competing risks using longitudinal modified treatment policies" [0.03%]
作者更正：纵向修改治疗政策下竞争风险的因果生存分析
Iván Díaz,Nicholas Williams,Katherine L Hoffman et al.
Iván Díaz et al.
The published version of the manuscript (D´iaz, Hoffman, Hejazi Lifetime Data Anal 30, 213-236, 2024) contained an error (We would like to thank Kara Rudolph for pointing out an issue that led to uncovering the error)) in the definition of...
A flexible Bayesian g-formula for causal survival analyses with time-dependent confounding [0.03%]
一种灵活的贝叶斯g公式用于时间依赖性混杂因素下的因果生存分析
Xinyuan Chen,Liangyuan Hu,Fan Li
Xinyuan Chen
In longitudinal observational studies with time-to-event outcomes, a common objective in causal analysis is to estimate the causal survival curve under hypothetical intervention scenarios. The g-formula is a useful tool for this analysis. T...
Lifetime analysis with monotonic degradation: a boosted first hitting time model based on a homogeneous gamma process [0.03%]
基于齐次伽马过程的递增退化寿命分析的首次击中模型及其加速方法
Clara Bertinelli Salucci,Azzeddine Bakdi,Ingrid Kristine Glad et al.
Clara Bertinelli Salucci et al.
In the context of time-to-event analysis, First hitting time methods consider the event occurrence as the ending point of some evolving process. The characteristics of the process are of great relevance for the analysis, which makes this cl...
A pairwise pseudo-likelihood approach for regression analysis of doubly truncated data [0.03%]
双截断数据回归分析的成对伪似然估计方法
Cunjin Zhao,Peijie Wang,Jianguo Sun
Cunjin Zhao
Double truncation commonly occurs in astronomy, epidemiology and economics. Compared to one-sided truncation, double truncation, which combines both left and right truncation, is more challenging to handle and the methods for analyzing doub...
Myrthe D&#x;Haen,Ingrid Van Keilegom,Anneleen Verhasselt
Myrthe D&#x;Haen
The study of survival data often requires taking proper care of the censoring mechanism that prohibits complete observation of the data. Under right censoring, only the first occurring event is observed: either the event of interest, or a c...
Goodness-of-fit testing in the presence of cured data: IPCW approach [0.03%]
存在免疫数据情况下的拟合优度检验：反概率重量法方法
Marija Cuparić,Bojana Milošević
Marija Cuparić
Here we revisit a goodness-of-fit testing problem for randomly right-censored data in the presence of cured subjects, i.e. the population consists of two parts: the cured or non-susceptible group, who will never experience the event of inte...
A global kernel estimator for partially linear varying coefficient additive hazards models [0.03%]
部分线性可变系数加性风险模型的全局核估计器
Hoi Min Ng,Kin Yau Wong
Hoi Min Ng
We study kernel-based estimation methods for partially linear varying coefficient additive hazards models, where the effects of one type of covariates can be modified by another. Existing kernel estimation methods for varying coefficient mo...
Gabriela Ciuperca
Gabriela Ciuperca
Based on the expectile loss function and the adaptive LASSO penalty, the paper proposes and studies the estimation methods for the accelerated failure time (AFT) model. In this approach, we need to estimate the survival function of the cens...
Proportional rates model for recurrent event data with intermittent gaps and a terminal event [0.03%]
具有间歇性间隙和终事件的复发事件数据的比例率模型
Jin Jin,Xinyuan Song,Liuquan Sun et al.
Jin Jin et al.
Recurrent events are common in medical practice or epidemiologic studies when each subject experiences a particular event repeatedly over time. In some long-term observations of recurrent events, a terminal event such as death may exist in ...
Walmir Dos Reis Miranda Filho,Fábio Nogueira Demarqui
Walmir Dos Reis Miranda Filho
We propose a new class of bivariate survival models based on the family of Archimedean copulas with margins modeled by the Yang and Prentice (YP) model. The Ali-Mikhail-Haq (AMH), Clayton, Frank, Gumbel-Hougaard (GH), and Joe copulas are em...