I have data from (1) different sessions of (2) different mice of (3) different laboratories. How can I analyze the data of different mice together and pool it while correcting for these three tiers of multiple comparisons?
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One approach is analysis of variance (ANOVA) which is a framework for analyzing mean differences while controlling for those effects. Typically a mixed-effect model is applied that handles experimental factors of both fixed and random-effects types, with appropriately different interpretations and analysis for the two types.
answered Sep 7, 2022 at 21:36
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$\begingroup$ Thanks Brian! The mixed-effect model sounds good. ANOVA tests the difference between two or more means, but I want something that does not rely exclusively on the mean but uses the entire signal. I tried Spearman-R correlation but also seems susceptible to noise. I'm thinking to try MMD. Do you know of any good tutorials to get started with the mixed-effect model? Many Thanks! $\endgroup$ Commented Sep 8, 2022 at 6:14