title: Assessing agreement with repeated measures for random observers.
abstract: Agreement studies are often concerned with assessing whether different observers for measuring responses on the same subject or sample can produce similar results. The concordance correlation coefficient (CCC) is a popular index for assessing the closeness among observers for quantitative measurements. Usually, the CCC is used for data without and with replications based on subject and observer effects only. However, we cannot use this methodology if repeated measurements rather than replications are collected. Although there exist some CCC-type indices for assessing agreement with repeated measurements, there is no CCC for random observers and random time points. In this paper, we propose a new CCC for repeated measures where both observers and time points are treated as random effects. A simulation study demonstrates our proposed methodology, and we use vertebral body data and image data for illustrations.
authors.affiliation: Section of Quantitative Health Sciences, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI 53226, USA. ccchen@mcw.edu
authors.forename: Chia-Cheng
authors.initials: CC
authors.lastname: Chen
authors.forename: Huiman X
authors.initials: HX
authors.lastname: Barnhart
mesh_terms: D056808:Biostatistics; D003198:Computer Simulation; D004452:Echocardiography / Q000706:statistics & numerical data; D006801:Humans; D009010:Monte Carlo Method; D015588:Observer Variation; D011859:Radiography; D011897:Random Allocation; D013131:Spine / Q000033:anatomy & histology / Q000000981:diagnostic imaging; D013997:Time Factors