Signal-to-noise ratio (SNR) as a measure of reproducibility: Design, estimation, and application

This paper proposes the use of signal-to-noise ratio (SNR) as another index of a measurement's reproducibility. We derive its maximum likelihood estimation and discuss confidence interval construction within the framework of the one-way random effect model. We investigate the validity of the approximate normal confidence interval by Monte-Carlo simulations. The paper also derives the optimal allocation for the number of subject and the number of repeated measurements needed to minimize the variance of the maximum likelihood estimator of the SNR. We discuss efficiency in estimation and cost considerations for the optimal allocation of the sample resources. The approach is illustrated on two examples: one from MRI data and the other on the WHO immunization coverage data. © Springer Science+Business Media, LLC 2008.