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The Power of Some Tests of Correlation

Published online by Cambridge University Press:  05 September 2017

Abstract

The coefficient of correlation between suitably defined statistics provides a means of testing various parametric hypotheses. The distribution of such coefficients, when the null hypothesis is not true, takes various forms in different applications. In particular, the correlation coefficients used to test hypotheses about the structural parameters in linear functional relations have doubly non-central distributions.

For tests of correlation in some typical situations, the curvature of the function defining the power in terms of the parameter in the neighbourhood of the null hypothesis is determined. This curvature is shown to be simply related to that of the function defining the squared correlation coefficient in terms of the parameter, in the neighbourhood of its minimum.

Type
Part III — Statistical Theory
Copyright
Copyright © 1975 Applied Probability Trust 

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References

[1] Delury, D. B. (1938) Note on correlations. Ann. Math. Statist. 9, 149151.Google Scholar
[2] Fisher, R. A. (1921) On the “probable error” of a coefficient of correlation deduced from a small sample. Metron 1, 332.Google Scholar
[3] Fisher, R. A. (1928) The general sampling distribution of the multiple correlation coefficient. Proc. Roy. Soc. A 121, 654673.Google Scholar
[4] Lehmann, E. L. (1959) Testing Statistical Hypotheses. Wiley, New York.Google Scholar
[5] Pitman, E. J. G. (1939) A note on normal correlation. Biometrika 31, 912.Google Scholar
[6] Pitman, E. J. G. (1949) Non-Parametric Statistical Inference. Columbia University Press.Google Scholar
[7] Tang, P. C. (1938) The power function of the analysis of variance tests with tables and illustrations of their use. Statist. Res. Memoirs 2, 126149.Google Scholar
[8] Williams, E. J. (1973) Tests of correlation in multivariate analysis. Bull. Int. Statist. Inst. 45, 219232.Google Scholar