Hunsberger Sally, Albert Paul S, Thoma Marie
Biostatistics Research Branch, 6130 Executive Blvd, rm 8120, Rockville, MD 20852, USA.
Biostatistics and Bioinformatics Branch, 6130 Executive Blvd, rm 8120, Rockville, MD 20852, USA,
Stat Interface. 2014;7(1):75-85. doi: 10.4310/SII.2014.v7.n1.a9.
For binary diseases that relapse and remit, it is often of interest to estimate the effect of covariates on the transition process between disease states over time. The transition process can be characterized by modeling the probability of the binary event given the individual's history. Designing studies that examine the impact of time varying covariates over time can lead to collection of extensive amounts of data. Sometimes it may be possible to collect and store tissue, blood or images and retrospectively analyze this covariate information. In this paper we consider efficient sampling designs that do not require biomarker measurements on all subjects. We describe appropriate estimation methods for transition probabilities and functions of these probabilities, and evaluate efficiency of the estimates from the proposed sampling designs. These new methods are illustrated with data from a longitudinal study of bacterial vaginosis, a common relapsing-remitting vaginal infection of women of child bearing age.
对于复发和缓解的二元疾病，估计协变量对疾病状态随时间变化的转换过程的影响通常很有意义。转换过程可以通过根据个体病史对二元事件的概率进行建模来表征。设计研究以随时间检查时变协变量的影响可能会导致收集大量数据。有时，收集和存储组织、血液或图像并回顾性分析此协变量信息是可行的。在本文中，我们考虑了不需要对所有受试者进行生物标志物测量的有效抽样设计。我们描述了转换概率及其函数的适当估计方法，并评估了所提出抽样设计估计的效率。这些新方法通过一项关于细菌性阴道病的纵向研究数据进行了说明，细菌性阴道病是育龄妇女常见的复发性阴道感染。
