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I love the inclusion of Chapter 11 as comparing predictive models with inferential models is something that is not done nearly enough in my field. However, I think it would be worth noting somewhere in this chapter that, if your data are multilevel, this nesting also needs to be accounted for in the inferential model. One approach would be to use cross-classified random effects (i.e., one for resample and one for cluster/multilevel-group). Eventually, it would be amazing to have {tidyposterior} intuit this nesting from your rsample object, but even still I think it is worth mentioning explicitly in the book.
The text was updated successfully, but these errors were encountered:
I love the inclusion of Chapter 11 as comparing predictive models with inferential models is something that is not done nearly enough in my field. However, I think it would be worth noting somewhere in this chapter that, if your data are multilevel, this nesting also needs to be accounted for in the inferential model. One approach would be to use cross-classified random effects (i.e., one for resample and one for cluster/multilevel-group). Eventually, it would be amazing to have {tidyposterior} intuit this nesting from your rsample object, but even still I think it is worth mentioning explicitly in the book.
The text was updated successfully, but these errors were encountered: