title: Double bootstrapping a tolerance limit.
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.
authors.affiliation: Johnson & Johnson Pharmaceutical Research and Development, LLC, Raritan, New Jersey, USA. JSHOUNG@prdus.jnj.com
authors.forename: Jyh-Ming
authors.initials: JM
authors.lastname: Shoung
authors.forename: Stan
authors.initials: S
authors.lastname: Altan
authors.forename: Javier
authors.initials: J
authors.lastname: Cabrera
mesh_terms: D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D004345:Drug Industry / Q000592:standards; D016018:Least-Squares Analysis; D015233:Models, Statistical; D011786:Quality Control