Spearman相关系数差异的显着性检验
我有一组人工评分的排名（HUMAN-RANKING），一组由当前使用的流行方法生成的排名（PRESENT-RANKING），最后一组由我的目的方法生成的排名（MY-RANKING） 。
我计算了人类排名和当前排名之间的斯皮尔曼相关性。 让我称之为：人类现身矛兵。
然后我发现了“人类排名”和“我的排名”之间的斯皮尔曼相关性。 让我称之为：人类我的矛兵。
如何确定 HUMAN-MY-SPEARMAN 和 HUMAN-PRESENT-SPEARMAN 之间的差异是否具有统计显着性？
提前致谢。
I have got a human-rated set of ranking (HUMAN-RANKING), a set of ranking generated by the presently used, popular method (PRESENT-RANKING), and finally a set of ranking generated by my purposed method (MY-RANKING).
I calculated the Spearman's correlation between HUMAN-RANKING and PRESENT-RANKING.
Let me call this: HUMAN-PRESENT-SPEARMAN.
I then found out the Spearman's correlation between HUMAN-RANKING and MY-RANKING.
Let me call this: HUMAN-MY-SPEARMAN.
How can I find out if the difference between HUMAN-MY-SPEARMAN and HUMAN-PRESENT-SPEARMAN is statistically significant?
Thanks in advance.
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你可以做所谓的费舍尔变换。 可以在此处找到链接。
一个问题是费舍尔变换假定统计独立性，但由于您在两个相关性中都使用了 HUMAN-RANKING，则违反了该假设。我不确定违反该假设会产生什么后果。
刚刚意识到这是十月的事情，所以它可能对你没有帮助，但我已经写了这篇文章。干杯。
You can do what is called Fisher transformation. A link can be found here.
One issue is that the Fisher transformation assumes statistical independence but since you are using HUMAN-RANKING in both correlations, that assumption is violated. I'm not sure what the consequences are from violating that assumption.
Just realized this was from October so it probably isn't helpful to you, but I had already written the post. Cheers.