Standard asymptotic chi-square distribution of the likelihood ratio and score statistics 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 component 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 proposed test has a significance level closer to the nominal one and it is more powerful. Copyright © Taylor & Francis Group, LLC
Samuh, M., Grilli, L., Rampichini, C., Salmaso, L., Lunardon, N. (2012). The use of permutation tests for variance components in linear mixed models. COMMUNICATIONS IN STATISTICS. THEORY AND METHODS, 41(16-17), 3020-3029 [10.1080/03610926.2011.587933].
The use of permutation tests for variance components in linear mixed models
LUNARDON, NICOLAUltimo
2012
Abstract
Standard asymptotic chi-square distribution of the likelihood ratio and score statistics 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 component 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 proposed test has a significance level closer to the nominal one and it is more powerful. Copyright © Taylor & Francis Group, LLCI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.