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You need to reshape the data from wide to long format first. One option for a solution is a linear mixed model. How can I test for the interaction I mentioned in R? Thanks a lot in advance.įirst, you aren't really "testing for homogeneity" you are testing for an interaction, it seems. I checked many forum posts, but the data set used in each experiment differed from mine, so it was hard to interpret the solutions (most include group, where my data is repeated measures). I am definitely not a stats wiz, and I am new to R. What I want to see is if the regression slope differences between low & high, differ for Cond 1 compared to Cond 2 (e.g., slopes are similar (between low & high) for Cond 1, but differ for Cond 2, which should be considered an interaction). I was told that testing for the homogeneity of regression slopes in ANCOVA can help me answer this question. What I want to do is to test for an interaction for how much the two levels (low & high) for each condition correlate with the covariate. There is also a covariate (a behavioral measure for how well they the participants did in a behavioral task). There are two conditions, each with two levels of a manipulation (2x2). The dependent variable is activation values (continous) from a specific brain site. I am analyzing data (see image below) from an fMRI experiment.
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