Abstract
Simulation studies are conducted to evaluate the performance of confidence intervals for variance components under non-normal distribution assumptions. Confidence intervals based on the pivotal quantity (PQ) method and the large-sample properties of the restricted maximum likelihood (REML) estimator are considered. Of particular interest is the actual coverage value of nominal 95% confidence intervals for a ratio of variance components. In the context of unbalanced one-way random effects models, simulation results and an empirical example involving arsenic concentrations in oyster tissue suggest that the REML-based confidence interval is preferred.
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