Bayesian inference for nonlinear mixed-effects location scale and interval-censoring cure-survival models: An application to pregnancy miscarriage.

IF 1.6 3区 医学 Q3 HEALTH CARE SCIENCES & SERVICES
Danilo Alvares, Cristian Meza, Rolando De la Cruz
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引用次数: 0

Abstract

Motivated by a pregnancy miscarriage study, we propose a Bayesian joint model for longitudinal and time-to-event outcomes that takes into account different complexities of the problem. In particular, the longitudinal process is modeled by means of a nonlinear specification with subject-specific error variance. In addition, the exact time of fetal death is unknown, and a subgroup of women is not susceptible to miscarriage. Hence, we model the survival process via a mixture cure model for interval-censored data. Finally, both processes are linked through the subject-specific longitudinal mean and variance. A simulation study is conducted in order to validate our joint model. In the real application, we use individual weighted and Cox-Snell residuals to assess the goodness-of-fit of our proposal versus a joint model that shares only the subject-specific longitudinal mean (standard approach). In addition, the leave-one-out cross-validation criterion is applied to compare the predictive ability of both models.

非线性混合效应的贝叶斯推断:位置尺度和间隔筛选治疗-生存模型:在妊娠流产中的应用。
在怀孕流产研究的激励下,我们提出了一个考虑到问题不同复杂性的纵向和事件时间结果的贝叶斯联合模型。特别是,纵向过程是通过具有特定对象误差方差的非线性规范来建模的。此外,胎儿死亡的确切时间尚不清楚,而且有一小部分妇女不易流产。因此,我们通过间隔截尾数据的混合治愈模型对生存过程进行建模。最后,这两个过程通过特定主题的纵向均值和方差联系在一起。为了验证我们的联合模型,进行了仿真研究。在实际应用中,我们使用个体加权和Cox-Snell残差来评估我们的建议与仅共享特定主题纵向平均值(标准方法)的联合模型的拟合优度。此外,采用留一交叉验证准则来比较两种模型的预测能力。
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来源期刊
Statistical Methods in Medical Research
Statistical Methods in Medical Research 医学-数学与计算生物学
CiteScore
4.10
自引率
4.30%
发文量
127
审稿时长
>12 weeks
期刊介绍: Statistical Methods in Medical Research is a peer reviewed scholarly journal and is the leading vehicle for articles in all the main areas of medical statistics and an essential reference for all medical statisticians. This unique journal is devoted solely to statistics and medicine and aims to keep professionals abreast of the many powerful statistical techniques now available to the medical profession. This journal is a member of the Committee on Publication Ethics (COPE)
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