Background

The number of studies using joint modelling of longitudinal and survival data have increased in the past two decades, but analytical techniques and software shortcomings have remained. A joint model is often used for analysis of a combination of longitudinal sub-model and survival sub-model using shared random effects. Cox regression commonly referring to the survival sub-model, should not be used when proportional hazards assumptions are not satisfied. In such cases, the parametric survival model is preferable.

Methods

We describe different parametric survival models for survival sub-model of joint modelling. We demonstrate how these models can be fit using gsem command (used for generalized structural equation model) in Stata that allows the model to be jointly continuous longitudinal and parametric survival data. With this code, linear mixed effect model is used for the longitudinal sub-model of the joint model, allowing random and fixed effects of the time. In gsem command for survival sub-models, there are five different choices: exponential, Weibull, log-normal, log-logistic and gamma accelerated failure time models.

Results

In this paper, we have described properties of gsem command for parametric joint modelling and have shown an application for parametric joint models on the 312 patients with primary biliary cirrhosis, which is a major health problem in the western world.

Conclusions

We showed how parametric joint models can be used with the gsem command which has been the only Stata code in the literature to fit the parametric joint models, for the generalized structural equation model, and we used the primary biliary cirrhosis dataset for the detailed application of the command. Thus, the gsem command becomes more useful for fitting parametric joint models.

中文翻译：

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gsem：用于纵向和加速故障时间模型的参数联合建模的Stata命令。

背景

在过去的二十年中，使用纵向和生存数据的联合模型进行研究的数量有所增加，但是分析技术和软件缺陷仍然存在。联合模型通常用于使用共享随机效应对纵向子模型和生存子模型的组合进行分析。当不满足比例风险假设时，不应使用通常指生存子模型的Cox回归。在这种情况下，参数生存模型是可取的。

方法

我们为联合建模的生存子模型描述了不同的参数生存模型。我们演示了如何使用Stata中的gsem命令（用于广义结构方程模型）拟合这些模型，该命令允许模型共同成为连续的纵向和参数生存数据。使用此代码，线性混合效果模型用于联合模型的纵向子模型，从而允许时间的随机和固定效果。在用于生存子模型的gsem命令中，有五个不同的选择：指数，威布尔，对数正态，对数逻辑和伽马加速故障时间模型。

结果

在本文中，我们描述了gsem命令用于参数化关节建模的属性，并展示了参数化关节模型在312例原发性胆汁性肝硬化患者中的应用，这是西方世界的主要健康问题。

结论

我们展示了如何将参数关节模型与gsem命令一起使用，gsem命令是文献中唯一适合参数关节模型的Stata代码，用于广义结构方程模型，并且我们使用了原发性胆汁性肝硬化数据集来详细应用命令。因此，gsem命令对于拟合参数关节模型变得更加有用。