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Generating random series with known values of Kendall's tau.

机译:生成具有肯德尔tau已知值的随机序列。

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Kendall's tau(a) offers statistical advantages to the more common Pearson's correlation and both are common in biomedical research. While generating random X-Y pairs from a known population value of Pearson's correlation is straightforward, the process for generating random sequences for a known value of Kendall's tau(a) is more complicated. Algorithms are presented that yield random numbers from a population with a known expected tau(a). They begin with a small set of values that have a known tau. These values are 'grown' to produce an arbitrarily large population that has the same expectation as the smaller set. Two examples are given. One example simulated samples from a population where tau(a) equaled 0.33 and confidence intervals are produced. A second example illustrates how the algorithm can be used to provide statistical power estimates for research studies using Kendall's tau(a).
机译:肯德尔的tau(a)为更常见的皮尔逊相关性提供了统计优势,并且两者在生物医学研究中都很常见。虽然从皮尔森相关性的已知总体值生成随机X-Y对很简单,但为肯德尔tau(a)的已知值生成随机序列的过程却更加复杂。提出了从预期tau(a)已知的种群中产生随机数的算法。它们以具有已知tau的一小部分值开始。这些值被“增长”,以产生任意数量的大群,其期望值与较小的期望值相同。给出两个例子。一个示例模拟了一个人口样本,其中tau(a)等于0.33,并产生了置信区间。第二个示例说明了如何使用该算法为使用肯德尔tau(a)的研究提供统计功效估计。

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