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AI 根据所提供的论文材料归类:摘要针对医学诊断准确性与潜变量混合模型,二元疾病状态并不足以归入经济离散选择或因果推断。

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代码、数据与补充材料

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关注这篇论文的作者
Yinsheng Qu
Alula Hadgu

不完美参照检验下相关诊断检验的灵敏度与特异度评估

研究问题
当多个诊断检验在疾病状态给定后仍相关,且参照检验有误甚至不存在时,如何估计和比较灵敏度与特异度?
方法与思路
作者构建含连续和二元潜变量的广义线性混合模型,以 EM 与 Newton–Raphson 混合算法进行最大似然估计,并纳入协变量效应。
材料陈述的贡献
摘要提出兼顾检验相关性和参照误分类的模型,并给出模型检查以及个体条件和总体平均灵敏度、特异度的估计与比较方法。
阅读关注点
应核对没有完美参照时的可识别条件、潜变量对相关性的刻画、算法收敛,以及个体条件指标与总体平均指标之间的转换。
阅读边界
仅据 OpenAlex 索引摘要,稿件版本未注明;潜变量分布与可识别条件未说明,不能认为缺少参照检验时总能可靠识别诊断准确性。

原文摘要

The purpose of a diagnostic efficacy study is to evaluate and compare the sensitivities and specificities of several diagnostic tests. Usually the diagnostic tests are correlated conditional on disease status, and the reference test is subject to error. In the Chlamydia trachomatis study, five screening tests for detecting chlamydia in endocervical specimens were compared. The five tests are correlated, and the reference test (the cell culture test) has less than 100% sensitivity. The conventional method ignores both the correlations between the tests and the misclassification of the reference test and thus cannot provide a valid analysis. We propose a model to evaluate and compare the sensitivities and specificities of correlated diagnostic tests when there is either an imperfect reference test or even no reference test. The model also can estimate the effects of covariates. It is a generalized linear mixed model with two unobserved variables, one continuous and one dichotomous. We use a hybrid algorithm, which consists of the EM algorithm and the Newton–Raphson method, for obtaining its maximum likelihood estimation. Methods for model checking and for estimating and comparing both subject-specific and population-averaged sensitivities and specificities are given.

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