贝叶斯方法估计诊断试验的时变敏感性及其在HIV母婴传播中的应用
Bayesian estimation of the time-varying sensitivity of a diagnostic test with application to mother-to-child transmission of HIV.
作者信息
Brown Elizabeth R
机构信息
Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA.
出版信息
Biometrics. 2010 Dec;66(4):1266-74. doi: 10.1111/j.1541-0420.2010.01398.x.
Abstract
We present a Bayesian model to estimate the time-varying sensitivity of a diagnostic assay when the assay is given repeatedly over time, disease status is changing, and the gold standard is only partially observed. The model relies on parametric assumptions for the distribution of the latent time of disease onset and the time-varying sensitivity. Additionally, we illustrate the incorporation of historical data for constructing prior distributions. We apply the new methods to data collected in a study of mother-to-child transmission of HIV and include a covariate for sensitivity to assess whether two different assays have different sensitivity profiles.
摘要
我们提出了一种贝叶斯模型，用于估计诊断检测随时间变化的灵敏度，该检测会随着时间反复进行，疾病状态在变化，且金标准仅部分可观察到。该模型依赖于疾病发病潜伏期分布和随时间变化的灵敏度的参数假设。此外，我们说明了如何纳入历史数据来构建先验分布。我们将新方法应用于在一项关于母婴传播艾滋病毒的研究中收集的数据，并纳入一个用于灵敏度的协变量，以评估两种不同检测方法的灵敏度曲线是否不同。
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