Weller S C, Mann N C
Department of Preventive Medicine and Community Health, University of Texas Medical Branch, Galveston 77555-1153, USA.
Med Decis Making. 1997 Jan-Mar;17(1):71-9. doi: 10.1177/0272989X9701700108.
This study illustrates the use of consensus theory to assess the diagnostic performances of raters and to estimate case diagnoses in the absence of a criterion or "gold" standard. A description is provided of how consensus theory "pools" information provided by raters, estimating rater competencies and differentially weighting their responses. Although the model assumes that raters respond without bias (i.e., sensitivity = specificity), a Monte Carlo simulation with 1,200 data sets shows that model estimates appear to be robust even with bias. The model is illustrated on a set of elbow radiographs, and consensus-model estimates are compared with those obtained from follow-up data. Results indicate that with high rater competencies, the model retrieves accurate estimates of competency and case diagnoses even when raters' responses are biased.
本研究阐述了如何运用共识理论评估评分者的诊断表现，并在缺乏标准或“金”标准的情况下估计病例诊断。文中描述了共识理论如何“汇总”评分者提供的信息，评估评分者能力并对他们的回答进行差异化加权。尽管该模型假设评分者的回答无偏差（即敏感度 = 特异度），但一项对1200个数据集的蒙特卡洛模拟表明，即使存在偏差，模型估计似乎也很稳健。该模型在一组肘部X光片上进行了演示，并将共识模型估计与从随访数据中获得的估计进行了比较。结果表明，当评分者能力较高时，即使评分者的回答存在偏差，该模型也能获得准确的能力估计和病例诊断。
