Joint analysis of bivariate longitudinal ordinal outcomes and competing risks survival times with nonparametric distributions for random effects
Joint analysis of bivariate longitudinal ordinal outcomes and competing risks survival times with nonparametric distributions for random effects
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DOI：
10.1002/sim.4507
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发表时间：
2012-07-20
影响因子：
2
通讯作者：
Tseng, Chi-Hong
中科院分区：
文献类型：
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作者：
Li, Ning;Elashoff, Robert M.;Tseng, Chi-Hong
我们提出了一个双变量纵向顺序结局和竞争风险失效时间数据的半参数联合模型。纵向和生存终点之间的关联通过潜在随机效应来捕获。这种方法概括了以前的联合分析，认为只有一个响应变量的纵向终点。该模型的一个独特之处是，我们放宽了随机效应常用的正态假设，并完全不指定分布。我们使用一个修改后的版本的顶点交换方法结合expectationmaximization算法来估计随机效应分布和模型参数。我们通过仿真表明，鲁棒的参数估计，从所提出的方法在各种情况下获得。我们使用硬皮病肺研究的咳嗽严重程度和频率数据来说明这种方法。版权所有（C）2012约翰威利父子有限公司
We propose a semiparametric joint model for bivariate longitudinal ordinal outcomes and competing risks failure time data. The association between the longitudinal and survival endpoints is captured by latent random effects. This approach generalizes previous joint analysis that considers only one response variable at the longitudinal endpoint. One unique feature of the proposed model is that we relax the commonly used normality assumption for random effects and leave the distribution completely unspecified. We use a modified version of the vertex exchange method in conjunction with an expectationmaximization algorithm to estimate the random effects distribution and model parameters. We show via simulations that robust parameter estimates are obtained from the proposed method under various scenarios. We illustrate the approach using cough severity and frequency data from a scleroderma lung study. Copyright (C) 2012 John Wiley & Sons, Ltd.