论文标题
测试合并单侧和双侧数据的比例平等
Testing the Equality of Proportions for Combined Unilateral and Bilateral Data
论文作者
论文摘要
在临床试验或观察性研究中，通常将测量值作为单侧或双侧数据收集。例如，在眼科研究中，统计检验通常基于一个人的一两只眼睛。对于双边数据，最近的文献显示了一些测试程序，这些测试程序考虑了同一人的两只眼睛之间的类内相关性。 Ma等。 （2015年）根据罗斯纳（Rosner）的模型研究了三个测试程序。在本文中，我们将MA的双边数据的工作扩展到了双边和单方面数据。所提出的程序基于从第四阶多项式方程和Fisher评分迭代的词根得出的可能性估计算法。进行仿真研究以比较不同参数配置下的测试程序。结果表明，得分测试具有令人满意的I型错误率和功率。因此，我们建议测试比例平等的得分测试。我们说明了提出的方法在双盲随机临床试验中的应用。
Measurements are generally collected as unilateral or bilateral data in clinical trials or observational studies. For example, in ophthalmologic studies, statistical tests are often based on one or two eyes of an individual. For bilateral data, recent literatures have shown some testing procedures that take into account the intra-class correlation between two eyes of the same person. Ma et al. (2015) investigated three testing procedures under Rosner's model. In this paper, we extend Ma's work for bilateral data to combined bilateral and unilateral data. The proposed procedures are based on the likelihood estimate algorithm derived from the root of 4th order polynomial equations and fisher scoring iterations. Simulation studies are performed to compare the testing procedures under different parameter configurations. The result shows that score test has satisfactory type I error rates and powers. Therefore, we recommend score test for testing the equality of proportions. We illustrate the application of the proposed methods with a double-blind randomized clinical trial.
