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Abstract
This paper presents a generalized variable approach for confidence interval estimation of a common correlation coefficient from several independent samples drawn from bivariate normal populations. This approach can provide one-sided bounds and two-sided confidence intervals with satisfying coverage probabilities regardless of the number of samples, sample sizes and magnitude of the common correlation coefficient while the large sample approach can be very liberal for one-sided bounds. The large sample approach generally performs well for two-sided confidence interval estimation.
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