Grant McDermott

@jparbache I don't quite follow. Are you just looking to change the scale of the predictions? If so, then that simply requires an appropriate `type = "link"` argument and works...

Hi @astraetech. Two quick points, both of which are documented in the [introductory vignette](https://lrberge.github.io/fixest/articles/fixest_walkthrough.html) and in the main help pages themselves. 1. fixest doesn't use/require 0 as a placeholder for...

> Is this the best way to approach? Nothing wrong with your general approach. But the idiomatic way to do this in fixest is by creating formula macros with [`xpd`](https://lrberge.github.io/fixest/reference/xpd.html)....

Hi @astraetech, > Those empty spaces would not be interepreted correctly by feols right? A formula with "" after a | would not treat that as no FE but that...

Sorry, missed this when it first came out. @frederickluser do you have a fake dataset that I could play around with to test?

This is great, thanks Jake. The problem with `aggregate` is that it doesn't necessarily work well for non-linear families. ``` r library(etwfe) data("mpdta", package="did") mpdta$emp = exp(mpdta$lemp) pmod = etwfe(...

+1 to @kylebutts and @s3alfisc's comments. OTOH—and apart from the non-linear family issue—the other tricky thing with the `aggregate.fixest` approach is that there isn't a straightforward way to recover an...

Hey @frederickluser sorry I completely missed this while I was on vacation. Just to say: That sounds very cool and I'm certainly interested in supporting anticipation effects if possible. I...

Indeed, I hadn't seen it. Thanks, will take a look!

Thanks! I've been neglecting this package, but will look into it when I get a chance. (Hoping to clean up the issues here once I finalize an upstream dependencies that...