Quantile dispersion graphs for the comparison of designs for a random two-way model

Juneyoung Lee, André I. Khuri

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


The choice of optimal designs for the estimation of variance components depends on the method of estimation, the model used, and the values of the variance components themselves. Traditional comparisons of such designs cannot therefore be made without some prior knowledge of the variance components. This problem was circumvented by the introduction of the so-called quantile dispersion graphs (QDGs) in Khuri (1997) and Lee and Khuri (1999). The present article provides an extension of the use of the QDGs to the comparison of designs for an unbalanced random two-way model without interaction. Two methods of estimation of the variance components are considered, namely, the analysis of variance (ANOVA) and maximum likelihood (ML).

Original languageEnglish
Pages (from-to)123-137
Number of pages15
JournalJournal of Statistical Planning and Inference
Issue number1
Publication statusPublished - 2000 Nov 1
Externally publishedYes


  • ANOVA estimation
  • Davies' algorithm
  • Maximum likelihood estimation
  • Primary 62J10
  • Secondary 62K99
  • Unbalanced design
  • Variance components

ASJC Scopus subject areas

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


Dive into the research topics of 'Quantile dispersion graphs for the comparison of designs for a random two-way model'. Together they form a unique fingerprint.

Cite this