I have a data set with thousands of pairs of cousins. There is a row for each cousin pair, with two columns: One column for the test score of one of the cousins in the pair, and one column with the test score of the other cousin. I want to calculate the correlation between cousins on this test. I could then just correlate the two columns. But I then worry that there would be problems related to the fact that many individuals have several different cousins, so that they are part of many of the rows in the data. Am I right to worry about this? What are the specific problems that can follow from this? And what are some more appropriate ways to calculate the correlation, which are computationally feasible for a dataset with hundreds of thousands of rows? (I'm hopeful that there are ways that do not involve dropping rows from the data until every individual are part of only one pair)
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1$\begingroup$ Are you saying you have data about people; that you group these people into nonoverlapping classes of "cousins;" and that you wish to study whether there is a tendency for groups of cousins to have more similar test scores than arbitrary groups? Or, as you seem to say, are these test scores somehow measuring some kind of joint characteristic of pairs of people? Could you explain what you mean by "the correlation" and which method of quantifying correlation you want to use (and why)? $\endgroup$whuber– whuber ♦2023-11-27 22:31:47 +00:00Commented Nov 27, 2023 at 22:31
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1$\begingroup$ Yes, I have data about people. They are grouped into pairs of cousins. I want to study the extent to which pairs of cousins are more similar than random pairings of people. Each test score is attached to just one person, so I'm not studying some kind of joint characteristic of pairs of people. What I mean by "the correlation": lets consider the correlation between monozygotic twins on height. This tends to be around .85. This means that if you know that one twin in a pair has a height that is 1 sd over the mean, then your best guess is that the other twin is .85 sd over the mean. $\endgroup$kaio– kaio2023-11-28 08:29:21 +00:00Commented Nov 28, 2023 at 8:29
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