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Using this limits of agreement framework, multivariate hierarchical Bayesian models provide an attractive alterative to the existing suite of analytic methods in measuring agreement using repeated measurement method comparison studies.
Until now, there have been no published Bayesian methods focusing on measurement method comparison studies.
This may be partly due to a lack of a flexible, easily implemented and readily available statistical machinery to analyse repeated measurement method comparison data.
Based on the limits of agreement approach framework, this paper advocates assessing agreement in repeated measurement method comparison studies using a fully parametric multivariate hierarchical Bayesian approach.
Measurement repeatability is important in measurement method comparison studies because it limits the amount of agreement which is possible [ 5, 8].
Repeated measurement method comparison studies quantify the agreement between the various methods under consideration and measure the agreement each method has to itself.
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The agreement of paired, quantitative measurements in method comparison or observer variation studies is often assessed with Bland-Altman plots with respective limits of agreement [3, 4].
The measurements for method comparison have to be performed at the same time to exclude subjective effects caused by changing user criteria rather than by the methods themselves.
Third, research nurses were trained in the delivery of the questionnaire, and finally, an objective measurement method was used for comparison.
Although units of measurement were different in each method, comparison of these true measures using the root mean square standard deviation (RMS SD) shown in Figure 3 indicates that deviation for the LPC and RET were similar for the same sites, except for the tibia where the LPC was higher than all other measures.
When looking at reported prevalence, this study shows the importance of noting the measurement method used before making comparisons, as it can vary considerably.
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