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We discussed adding a "batch" variable in the individual regression to alleviate some violation of the independence assumption (hence the term pseudo). For example, a diff between sample 3 and 2 would have 3 as the batch number (rule of thumb: take the first sample id).
I thought about considering this variable as a random effect term, but the independence assumption there is not quite what we want. For instance, within the neighborhood of 3, these differences (e.g. 3-2, 3-5, 3-6) are independent. However, they may not be independent of other differences in a different neighborhood (e.g. 2-5). In short, we have within-neighborhood independence but not between-neighborhood (which a mixed model would correct for).
Maybe we should stick with the fixed model and adding the batch variable as a fixed effect term.
The text was updated successfully, but these errors were encountered:
I will plan on adding a boolean flag to the main function, maybe called dependent.neighbors.adjust. When True, it will create the covariate dependent.neighbors.covar and add it to the model to adjust for dependency. I have an idea to run by you for dependent.neighbors.covar to capture the redundancy. It will be a lot of states for a factor variable.
We discussed adding a "batch" variable in the individual regression to alleviate some violation of the independence assumption (hence the term pseudo). For example, a diff between sample 3 and 2 would have 3 as the batch number (rule of thumb: take the first sample id).
I thought about considering this variable as a random effect term, but the independence assumption there is not quite what we want. For instance, within the neighborhood of 3, these differences (e.g. 3-2, 3-5, 3-6) are independent. However, they may not be independent of other differences in a different neighborhood (e.g. 2-5). In short, we have within-neighborhood independence but not between-neighborhood (which a mixed model would correct for).
Maybe we should stick with the fixed model and adding the batch variable as a fixed effect term.
The text was updated successfully, but these errors were encountered: