A model is presented that describes bivariate longitudinal count data by conditioning on a progressive illness-death process where the two living states are latent. The illness-death process is modelled in continuous time, and the count data are described by a bivariate extension of the binomial distribution. The bivariate distributions for the count data approach include the correlation between two responses even after conditioning on the state. An illustrative data analysis is discussed, where the bivariate data consist of scores on two cognitive tests, and the latent states represent two stages of underlying cognitive function. By including a death state, possible association between cognitive function and the risk of death is accounted for.

中文翻译：

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用于双变量纵向计数数据的隐藏三态生存模型。

提出了一个模型，该模型通过以疾病的渐进性疾病死亡过程为条件来描述双变量纵向计数数据，在该过程中，两种生活状态都是潜在的。在连续时间内对疾病死亡过程进行建模，并通过二项式分布的二元扩展来描述计数数据。计数数据方法的双变量分布包括两个响应之间的相关性，即使在对状态进行条件化之后也是如此。讨论了说明性的数据分析，其中双变量数据由两个认知测验的分数组成，而潜在状态表示基础认知功能的两个阶段。通过包括死亡状态，可以说明认知功能与死亡风险之间的可能关联。