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Aug 15, 2022 at 23:20 comment added Glen_b 1. It shouldn't lose much efficiency wise if both the conditions I mentioned hold; otherwise I wouldn't do it. 2. There is a question - I should have mentioned it before - of why there were some unpaired values. e.g. If those were missing not at random, you have to carefully consider the biases involved in handling the overlapping samples.
Aug 15, 2022 at 15:18 comment added Najeha Mohamed thank you so much for your input! just exactly what i was looking for. Is it okay to perform tests without the independent samples?
Aug 15, 2022 at 15:17 comment added Najeha Mohamed thank you so much for your input! just exactly what i was looking for. Is it okay to perform tests without the independent samples?
Aug 15, 2022 at 10:18 comment added Glen_b This situation is sometimes called (partially) overlapping samples and tests for it are called (partially) overlapping samples tests. e.g. see cran.r-project.org/web/packages/Partiallyoverlapping . The manual has references. (When the within-pair dependence is strong and the paired observations comprise most of the data, the independent observations might not tend to add a lot of information to what you get with the paired data.) ... also see tqmp.org/RegularArticles/vol18-1/p055/p055.pdf ... These should give you further references and suitable search terms.
Aug 15, 2022 at 9:42 history asked Najeha Mohamed CC BY-SA 4.0