On the Sub-D's mean square error on one-way random designs

Research output: Contribution to journalArticlepeer-review

Abstract

Through simulations, it was shown that either in balanced 'one-way' random designs or in unbalanced 'one-way' random designs, Sub-D estimates are in general more accurate than those provided by Anova-based estimators. Moreover, the Sub-D estimates exhibit less dispersion magnitude. Such estimates reveal to be also slightly more accurate than those provide by REML-based estimator, although this latter one presented dispersion with slightly less magnitude, which, indeed, is not bigger than 0.0261. In order to have somehow a robust tool which will allow us to infer over Sub-D's efficiency in 'one-way' random designs, this paper aims to deduce and discuss its MSE.

Original languageEnglish
Pages (from-to)117-123
Number of pages7
JournalModel Assisted Statistics and Applications
Volume16
Issue number2
DOIs
Publication statusPublished - 2021

Keywords

  • efficiency
  • MSE
  • Sub-D
  • Variance components

Fingerprint

Dive into the research topics of 'On the Sub-D's mean square error on one-way random designs'. Together they form a unique fingerprint.

Cite this