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AI 根据所提供的论文材料归类:摘要明确研究同一受试者跨时间的重复诊断及不规则观测,直接涉及纵向数据建模。

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关注这篇论文的作者
Mark A. Espeland
Orah S. Platt
Dianne Gallagher

不规则纵向数据中发生率与诊断误差率的联合估计

研究问题
对诊断时间不规则且可能误判的渐进性分类过程,如何区分真实状态变化与诊断错误,并联合估计发生率和误差率?
方法与思路
作者联合参数化发生率与诊断误差,使用 EM 算法进行最大似然估计,并以似然比检验分析分类协变量的关系。
材料陈述的贡献
摘要称,方法可处理个体间不同的不规则诊断时间;疾病数据分析显示成熟延迟、误差率随年龄变化及误判方向差异。
阅读关注点
应核对真实进程与诊断误差的可识别条件、误差依赖结构、EM 实现,以及年龄相关误差结论对模型设定的敏感性。
阅读边界
摘要未说明完整识别条件或效应数值,病例分析不能据此作因果判断;所给 OpenAlex 索引摘要未注明稿件版本。

原文摘要

Longitudinal studies often involve the repeated diagnosis across time of each patient's status with respect to a progressive categorical process. When the occurrence of a change in status is not readily apparent, two factors can make modeling and assessing the incidence rates of progression difficult. First, because diagnoses may be difficult, they may not be performed with the frequency necessary to pinpoint exact times of incidence. Second, uncertainty in the diagnostic process can obscure identification of the time interval in which incidence occurs. When serial diagnoses are fallible, even small error rates can seriously disrupt interpretation and make using the aforementioned methods difficult or impossible. For example, if false diagnoses (both false positives and negatives) occur independently with probability .05 in a longitudinal study involving four serial diagnoses, 19% of the strings of serial diagnoses would be expected to contain at least one error. If the underlying process is progressive, many of these errors would be noticeable: At face value, some patterns of diagnoses would describe regressions. Errors yielding patterns of diagnoses that are progressive would not be detectable. Simply omitting any subjects with inconsistent patterns from the analysis introduces bias. Another possible approach, using the first reported incidence of progression, also introduces bias (Schlesselman 1977). To analyze clinical data on the diagnosis of sexual maturation among subjects with sickle-cell disease, models are developed for jointly parameterizing incidence and error rates. An EM algorithm is presented that allows tractable maximum likelihood estimation even when the times of diagnoses are irregular and vary among subjects. Likelihood ratio tests are used to assess relationships between categorical covariates and both incidence and error rates. Data from the Cooperative Study of Sickle Cell Disease are analyzed to describe the age distribution for the onset of puberty (according to the Tanner stage index) among homozygous (SS) males. Clear delays in maturation are apparent among SS males. Diagnostic error rates for Tanner staging appear to vary with the subject's age. False-positive diagnoses appear to be more common than false-negative diagnoses.

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