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On the Optimality of F ‐test on Variance Components in Mixed Linear Models
Author(s) -
Roebruck P.
Publication year - 1982
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710240811
Subject(s) - mathematics , variance components , mixed model , linear model , statistics , variance (accounting) , minimum variance unbiased estimator , best linear unbiased prediction , generalized linear mixed model , random effects model , econometrics , computer science , mean squared error , accounting , business , medicine , selection (genetic algorithm) , meta analysis , artificial intelligence
Abstract The analysis‐of‐variance tests for hypotheses on random effects in regular linear models are considered. Conditions are given for these tests to be uniformly most powerful unbiased or uniformly most powerful invariant unbiased. An example shows that the difference between these conditions can be serious.