%0 Generic %A X Barnhart, Huiman %D 2016 %T Data from: Assessing agreement with relative area under the coverage probability curve %U https://wiley.figshare.com/articles/dataset/Data_from_Assessing_agreement_with_relative_area_under_the_coverage_probability_curve/2077594 %R 10.6084/m9.figshare.2077594.v1 %2 https://wiley.figshare.com/ndownloader/files/3709765 %K Agreement %K Reliability %K Measurement Error %K Coverage Probability %K Area under the curve %K Medicine %K Statistics %X There has been substantial statistical literature in the last several decades on assessing agreement and coverage probability approach was selected as a preferred index for assessing and improving measurement agreement in a core laboratory setting [1]. With this approach, a satisfactory agreement is based on pre-specified high satisfactory coverage probability (e.g., 95%), given one pre-specified acceptable difference. In practice, we may want to have quality control on more than one pre-specified differences or we may simply want to summarize the agreement based on differences up to a maximum acceptable difference. We propose to assess agreement via the coverage probability curve that provides a full spectrum of measurement error at various differences/disagreement. Relative area under the coverage probability curve is proposed for the summary of overall agreement and this new summary index can be used for comparison of different intra- or inter-methods/labs/observers’ agreement. Simulation studies and a blood pressure example are used for illustration of the methodology.
%I Wiley