Digitale et al 2022. Tutorial on DAGs. doi.org/10.1016/j.jc....doi.org/10.1001/jama...doi.org/10.1098/rspb...doi.org/10.1093/ije/...
This one I wrote for my students. They are graduates, but it is fairly self-contained, and one of the goals was to correct some erroneous beliefs that psychology graduates tend to have. Judea Pearl seemed to like it (he recommended it on Twitter) czasopisma.uwm.edu.pl/index.php/pp...
I know this is an annoying remark, but I think when ppl see the hashtag #stats they may think this is a statistical problem. This important problem cannot even be defined, let alone successfully addressed, without introducing causal notions & these are provably non-reducible to statistical notions.
See here, on page 230 czasopisma.uwm.edu.pl/index.php/pp...
If you didn't know, now you know: In general causal graphs, X>Y by default means "X may or may not cause Y," which means "I don't know" (in classical logic), but in *acyclic* graphs an arrow is a *stronger* assumption than an absence of an edge: if X>Y then not Y>X but not Y>X says nothing about X>Y
💯 Especially if "methodological" is understood as including logic / definitions+argument structure.
If you want to find out whether something has been replicated, you can also go to forrt-replications.shinyapps.io/fred_explorer/, choose all studies, and enter a search term. We try to keep track of all replication attempts.
academic papers should include an "Author's Cut" button that easily toggles between the paper they wanted published, and the version with all the stuff forced on them to get it through review
There will forever be a soft spot in my heart for Linear Algebra Done Right (I especially like the 2nd ed.), but I recently discovered this series of blog posts, and I am not sure if this will not soon become a favorite: graphicallinearalgebra.net
Visit the post for more.