The use of permutation tests for variance components in linear mixed models

Standard asymptotic chi-square distribution of the likelihood ratio and score statis- tics under the null hypothesis does not hold when the parameter value is on the boundary of the parameter space. In mixed models it is of interest to test for a zero random effect variance component. Some available tests for the variance compo- nent are reviewed and a new test within the permutation framework is presented. The power and significance level of the different tests are investigated by means of a Monte Carlo simulation study. The level of the proposed test is closer to the nominal significance level and is more powerful.