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Biometrika 1973 60(3):551-558; doi:10.1093/biomet/60.3.551
© 1973 by Biometrika Trust
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A Monte-Carlo study of asymptotically robust tests for correlation coefficients

G. T. DUNCAN and M. W. J. LAYARD

University of California Davis

Monte-Carlo simulation is used to compare the small-sample performance of the usual normal theory procedures for inference about correlation coefficients with that of two asymptotically robust procedures, one of which is based on a grouping of the observations and the other on the jackknife technique. The sampled distributions comprise the normal and five nonnormal distributions. The small-sample results support the conclusion based on asymptotic theory that the normal test is not robust. The jackknife procedure works well for most of the sampled distributions.

Key Words: Correlation coefficients • Hypothesis testing • Confidence intervals • Robustness • Large sample theory • Jackknife


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