Abstract
We consider the problem of constructing tolerance limits in the context of a one-way random effects model. The usual parametric method for calculating tolerance intervals is based on the normality assumption. However, in practice, we frequently observe nonnormally distributed data. We propose the use of the double bootstrap (or nested bootstrap) method to estimate tolerance limits, which allows us to relax the normality assumption.