I know the pro version of Claude will let me load up papers, that’s the next approach I’ll take

I tried similar prompts with the Assistant in SCite, but it gave errors and didn’t produce anything. I think it does better with shorter prompts (“find references to support / disagree with this statement”)

(@scite.bsky.social exists, but I can't tag it)

When I finally got it to make citations in the style I wanted, many of them were incorrect (which is wild, when there are only 40 or so papers loaded).

In the end, it didn’t save me any time at all

It writes OK lit review text, but I can’t get it to make usable citations. It makes those little numbers I can hover over, but it’s a ton of manual work to turn those into \cite{xyz} commands.

A lot of complaints about similar issues online: www.reddit.com/r/notebooklm...

It’s really funny, though not a comedy

Here’s a paper doing imputation. I read and earlier version, not the latest, and was frustrated that they didn’t compare their ML imputation method to other more traditional imputation approaches.

arxiv.org/pdf/2305.096...

This is the closest I’ve found:

arxiv.org/abs/2401.08572

How do you make a scientific case about a method’s usefulness without a proper lit review?

by synthetic samples, I mean using LLMs to generate survey responses

"imagine you are a 54 year old African American man. Please answer the following survey question..."

IMO, the worst problem with data analysis a in Excel is how hard it is to trace back where a result came from. Yes, there are now trace dependence and trace precedence buttons, but it still is not nearly as clear as it would be in a script file

They really are : “the importance…in some vague sense” IIRC

I show students the definitions of the 4 types of weights, to try to prevent them from using aw= (because that’s what the command accepts) when they have pweights. I doubt I’m successful

Debatable — what do you mean by “very well”?

Sort of — in R, PLmixed will give you similar results (discrimination, difficulty) to mirt. PLmixed fits “mixed models with factor structures”

because they're economists 😉?