A tolerance interval approach for assessment of agreement with left censored data

We describe a tolerance interval approach for assessing agreement in method comparison data that may be left censored. We model the data using a mixed model and discuss a Bayesian and a frequentist methodology for inference. A simulation study suggests that the Bayesian approach with noninformative priors provides a good alternative to the frequentist one for moderate sample sizes as the latter tends to be liberal. Both may be used for sample sizes 100 or more, with the Bayesian one being slightly conservative. The proposed methods are illustrated with real data involving comparison of two assays for quantifying viral load in HIV patients.