We observe a quarter million people over a period of nine years and are interested in the effect of a stroke on the probability of dementia onset. Randomly left-truncated has a person been that was already deceased before the period. The ages at a stroke event or dementia onset are conditionally fixed right-censored, when either event may still occur, but after the period. We incorporate death and model the history of the three events by a homogeneous Markov process. The compensator for the respective counting processes is derived and Jacod's formula yields the likelihood contribution, conditional on observation. An Appendix is devoted to the role of filtrations in deriving the likelihood, for the simplification of merged non-dead states. Asymptotic normality of the estimated intensities is derived by martingale theory, relative to the size of the sample including the truncated persons. The data of a German health insurance reveals that after a stroke, the intensity of dementia onset is increased from 0.02 to 0.07, for Germans born in the first half on the 20th century. The intensity difference has a 95%-confidence interval of [0.048,0.051] and the difference halves when we extent to an age-inhomogeneous model due to Simpson's paradox.
翻译:在9年的时间里,我们观察了25万人口,并且对中风对痴呆发作概率的影响感兴趣。 随机左转的人在这段时间之前已经去世了。 中风或痴呆发作的年龄是有条件的固定的右检查年龄, 当任一事件可能仍然发生时, 但是在这段时期之后。 我们用一个单一的Markov 程序将死亡和三个事件的历史模型纳入其中。 分别计算过程的补偿者是推算出来的, Jacod 的公式以观察为条件, 产生可能的贡献。 附录专门说明过滤作用的作用, 以简化合并的非死状态为条件。 估计的强度的常态性是有条件的固定的, 与样本的大小相比, 包括被挤压的人。 德国健康保险的数据表明, 中风后, 痴呆发作的强度从0.02 上升到0.0 。 对于20世纪上半出生的德国人来说, 其作用是过滤作用的作用。 强烈性差异在20世纪前半的德国人之间, 程度为95. 0 之间的信任度 。