Estimation for a common intraclass correlation in bivariate normal distributions with missing observations

Mihoko Minami, Kunio Shimizu

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

The maximum likelihood estimate and the restricted or residual maximum likelihood estimate are considered for a common intraclass correlation coefficient among several bivariate normal distributions when some observations on either of the variables are missing. The estimates are given as the solutions of polynomial equations. Asymptotic variances of both estimates are obtained from the corresponding information matrices. The variance stabilizing transformation, which can be used to perform hypothesis tests and construct a confidence interval for ρ, is derived.

Original languageEnglish
Pages (from-to)3-14
Number of pages12
JournalAmerican Journal of Mathematical and Management Sciences
Volume17
Issue number1-2
DOIs
Publication statusPublished - 1997 Jan 1
Externally publishedYes

Keywords

  • Asymptotic variance
  • Fisher information matrix
  • MLE
  • REMLE
  • Variance stabilizing transformation

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Applied Mathematics

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