A new likelihood approach to inference about predictive values of diagnostic tests in paired designs
A new likelihood approach to inference about predictive values of diagnostic tests in paired designs
复制标题
推断配对设计中诊断测试的预测值的新似然方法
DOI：
10.1177/0962280216634755
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发表时间：
2018
影响因子：
2.3
通讯作者：
Tsung
中科院分区：
文献类型：
--
作者：
Tsung
直观上，只需要两次筛查试验结果为阳性的患者进行阳性预测值比较，两次筛查试验结果为阴性的患者进行阴性预测值对比。然而，目前现有的方法依赖于多项模型，其中包括多余的参数，而这些参数对于具体的比较来说是不必要的。这种做法产生了复杂的统计公式。我们引入了一种新颖的似然方法，通过在配对设计中包含最小数量的感兴趣参数来拟合直觉。结果表明，我们的稳健分数检验统计量与新提出的加权广义分数检验统计量相同。通过仿真和实际数据分析进行说明。
Intuitively, one only needs patients with two positive screening test results for positive predictive values comparison, and those with two negative screening test results for contrasting negative predictive values. Nevertheless, current existing methods rely on the multinomial model that includes superfluous parameters unnecessary for specific comparisons. This practice results in complex statistics formulas. We introduce a novel likelihood approach that fits the intuition by including a minimum number of parameters of interest in paired designs. It is demonstrated that our robust score test statistic is identical to a newly proposed weighted generalized score test statistic. Simulations and real data analysis are used for illustration.