Applying Skovgaard's modified directed likelihood statistic to mixed linear models

Ben Lyons, Dawn Peters

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

The introduction of software to calculate maximum likelihood estimates for mixed linear models has made likelihood estimation a practical alternative to methods based on sums of squares. Likelihood based tests and confidence intervals, however, may be misleading in problems with small sample sizes. This paper discusses an adjusted version of the directed log-likelihood statistic for mixed models that is highly accurate for testing one parameter hypotheses. Introduced by Skovgaard (1996, Journal of the Bernoulli Society, 2, 145-165), we show in mixed models that the statistic has a simple compact form that may be obtained from standard software. Simulation studies indicate that this statistic is more accurate than many of the specialized procedures that have been advocated.

Original languageEnglish (US)
Pages (from-to)225-242
Number of pages18
JournalJournal of Statistical Computation and Simulation
Volume65
Issue number3
DOIs
StatePublished - Jan 1 2000

Keywords

  • Asymptotics
  • Likelihood
  • Mixed models
  • Repeated measures
  • Small sample inference
  • Variance components

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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