A REMARK ON TESTING SIGNIFICANCE OF AN OBSERVED CORRELATION MATRIX

Shande Chen And; Govind S. Mudholkar

doi:10.1111/j.1467-842X.1989.tb00503.x

A REMARK ON TESTING SIGNIFICANCE OF AN OBSERVED CORRELATION MATRIX

Shande Chen And, Govind S. Mudholkar

School of Public Health

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

A simple test for the diagonality of the covariance matrix of a multi‐variate normal population is proposed. The test, which is based upon the sum of squares of the z‐transforms of the sample correlations, is seen to compare well with the current tests in terms of both the null distribution approximations and the powers.

Original language	English
Pages (from-to)	105-110
Number of pages	6
Journal	Australian Journal of Statistics
Volume	31
Issue number	1
DOIs	https://doi.org/10.1111/j.1467-842X.1989.tb00503.x
State	Published - Mar 1989

Keywords

complete independence
pairwise independent correlations
x approximation
z‐transformation

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10.1111/j.1467-842X.1989.tb00503.x

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abstract = "A simple test for the diagonality of the covariance matrix of a multi‐variate normal population is proposed. The test, which is based upon the sum of squares of the z‐transforms of the sample correlations, is seen to compare well with the current tests in terms of both the null distribution approximations and the powers.",

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AB - A simple test for the diagonality of the covariance matrix of a multi‐variate normal population is proposed. The test, which is based upon the sum of squares of the z‐transforms of the sample correlations, is seen to compare well with the current tests in terms of both the null distribution approximations and the powers.

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A REMARK ON TESTING SIGNIFICANCE OF AN OBSERVED CORRELATION MATRIX

Abstract

Keywords

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