On optimum invariant tests of equality of intraclass correlation coefficients

DOI10.1007/BF00773357zbMath0805.62021OpenAlexW2046915371MaRDI QIDQ1335361

Wen-Tao Huang, Bimal Kumar Sinha

Publication date: 6 February 1995

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00773357

zbMATH Keywords

tablesinvarianceoptimalityapproximate likelihood ratio testsapproximately optimum invariant testsFisher's \(Z\)-testsLMMPIU testlocally most powerful invariant unbiased testtesting the equality of \(k\) intraclass correlation coefficientsUMPIU testuniformly most powerful invariant unbiased test

Mathematics Subject Classification ID

Parametric hypothesis testing (62F03) Foundations and philosophical topics in statistics (62A01)

Related Items (5)

Test for the equality of interclass correlation cofefficients under unequal family sizes for several populations ⋮ CONFIDENCE INTERVAL ESTIMATION FOR A DIFFERENCE BETWEEN TWO INTRACLASS CORRELATION COEFFICIENTS UNDER UNEQUAL FAMILY SIZES ⋮ Confidence interval estimation for a linear contrast in intraclass correlation coefficients under unequal family sizes for several populations ⋮ A Small Sample Test for the Equality of Intraclass Correlation Coefficients Under Unequal Family Sizes for Several Populations ⋮ On optimal testing for the equality of equicorrelation: An example of loss in power

Cites Work

• Normalizing and variance stabilizing transformations for intraclass correlations
• Optimal tests for the correlation coefficient in a symmetric multivariate normal population
• Testing the equality of several intraclass correlation coefficients
• Inferences Concerning a Common Intraclass Correlation Coefficient
• Alternative Models for the Analysis of Variance
• Estimation of interclass correlations in familial data
• Locally Optimal Tests for Multiparameter Hypotheses
• Significance Testing of Interclass Correlations from Familial Data
• Linear Statistical Inference and its Applications
• On the Theory of Unbiased Tests of Simple Statistical Hypotheses Specifying the Values of Two or More Parameters
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