Statistical methods for panel data from a semi-Markov process, with application to HPV
Statistical methods for panel data from a semi-Markov process, with application to HPV
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DOI：
10.1093/biostatistics/kxl006
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发表时间：
2007-04-01
期刊：
影响因子：
2.1
通讯作者：
Lagakos, Stephen W.
中科院分区：
文献类型：
--
作者：
Kang, Minhee;Lagakos, Stephen W.
连续时间，多态过程可以用来代表各种生物过程在公共卫生科学，但这种过程的分析是复杂的，当他们只在有限数量的时间点观察。这种面板数据的推断方法已经开发了时间齐次马尔可夫模型，但很少有研究做其他类别的过程。我们开发了基于似然性的方法，面板数据从半马尔可夫过程，过渡强度取决于在当前状态的持续时间。所提出的方法占可能的错误分类的状态。为了说明这些方法，我们详细研究了三态和四态模型，并将结果应用于模拟女性生殖器致癌性人乳头瘤病毒感染的自然史。
Continuous-time, multistate processes can be used to represent a variety of biological processes in the public health sciences; yet the analysis of such processes is complex when they are observed only at a limited number of time points. Inference methods for such panel data have been developed for time homogeneous Markov models, but there has been little research done for other classes of processes. We develop likelihood-based methods for panel data from a semi-Markov process, where transition intensities depend on the duration of time in the current state. The proposed methods account for possible misclassification of states. To illustrate the methods, we investigate a three- and a four-state models in detail and apply the results to model the natural history of oncogenic genital human papillomavirus infections in women.