TY - UNPB
T1 - Bootstrapping F test for testing random effects in linear mixed models
AU - O’Shaughnessy, P. Y.
AU - Hui, F. K. C.
AU - Muller, Samuel
AU - Welsh, Alan H.
PY - 2018
Y1 - 2018
N2 - Recently Hui et al. (2018) use F tests for testing a subset of random effect, demonstrating its computational simplicity and exactness when the first two moment of the random effects are specified. We extended the investigation of the F test in the following two aspects: firstly, we examined the power of the F test under non-normality of the errors. Secondly, we consider bootstrap counterparts to the F test, which offer improvement for the cases with small cluster size or for the cases with non-normal errors.
AB - Recently Hui et al. (2018) use F tests for testing a subset of random effect, demonstrating its computational simplicity and exactness when the first two moment of the random effects are specified. We extended the investigation of the F test in the following two aspects: firstly, we examined the power of the F test under non-normality of the errors. Secondly, we consider bootstrap counterparts to the F test, which offer improvement for the cases with small cluster size or for the cases with non-normal errors.
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85094534691&partnerID=MN8TOARS
U2 - 10.48550/arXiv.1812.03428
DO - 10.48550/arXiv.1812.03428
M3 - Preprint
T3 - arXiv
BT - Bootstrapping F test for testing random effects in linear mixed models
PB - arXiv.org
ER -