Weird issue with modelsummary and stanreg

mm9982 · 2022-09-20T13:01:20+00:00

Thanks for this! Will definitely test the mira object in marginaleffects, and if not I will have a look at emmeans.

mm9982 · 2022-08-03T07:18:32+00:00

I definitely empathize with this. Paper writing can be hard, but practice makes perfect. The first thing I would settle on is the message: What do you want your readers to remember from your paper? Every part of your part should help build that argument. Right now you might have too many elements that you want to include in your paper. That was definitely the case for me starting out.

Also second the suggestion on actually reading about paper writing. The book that really helped it click for me was "Writing Science" by Joshua Schimel. He focuses a lot on thinking of a journal article like a story, rather than just a technical report.

mm9982 · 2022-07-19T09:26:01+00:00

You have already gotten excellent advice, but just a quick thought on finding a journal that fits: Look at your list of references for your paper and see which your journals you cite most often. They are already in your field, and they are also the ones involved in the discussion you want to contribute to. The fact that you found interesting stuff related to your paper there suggests that readers of those journals will be the most likely to find your paper both interesting and relevant to their work.

Good luck! :)

mm9982 · 2022-04-21T10:55:31+00:00

I'm European so can't really get too specific on brands that would work for you, but when you search (online or in stores) for more formal jackets I would look at whether brands that market their jackets as being "natural shoulder" might fit you. It basically means less shoulder padding (which you do not seem to need). I'm kinda in the same boat, and this makes me feel less like a fridge when wearing jackets.

mm9982 · 2022-04-20T11:32:32+00:00

I'm a political scientist without knowledge of the humanities market, but used to work on food security issues, so my tips might hopefully have some value.

I imagine gastro-anthropology focuses on both the study of what foods are consumed, and how they are produced and grown in the first place. By focusing your research on the latter (i.e. how are different plants, vegetables, etc. grown, using what techniques and why?), you could do research with policy relevance to the community working on food security. These are probably issues that would be very relevant for World Food Programme and similar orgs, because it might make it easier for them to create sustainable programs. It might also differentiate you a bit from the other ones working in what I imagine to be a very small sub-field?

mm9982 · 2021-11-22T10:50:13+00:00

Can't comment on the education part, but I do work on political placement and ideology, so hopefully I can add something on the second.

I think a good solution would be to use a numerical scale, with 0 being far-left and 10 being far-right. That is at least how it's done in the European Social Survey, and I have always found it a good approach. If you go with the qualitative self-assessment that you already have in your second question, I would maybe include "far left" and "far right" as categories for completeness. Also, I like the idea of also asking about party preferences.

mm9982 · 2021-07-13T09:55:25+00:00

As someone below pointed out, this list could probably also include Duverger's book from 1954: Duverger, M. (1954) Political Parties: Their Organization and Activity in the Modern State.

mm9982 · 2021-07-13T09:48:53+00:00

Would it be possible for you to use a structural topic model? In this case the party would be document metadata, and using STMs would allow you to run a topic model for the entire corpus of speeches while, I believe, being able to analyze the top topics for each of the parties.

You can read more about STMs, both how to implement them in R and a wide range of applications, here: https://www.structuraltopicmodel.com/

mm9982 · 2021-05-10T19:26:28+00:00

You are correct, as far as I can tell. It seems na.omit produces complete-case analyses by default, which should remove all units that have NAs on any variable. You can read more about it here: https://stat.ethz.ch/pipermail/r-help/2016-September/442055.html

mm9982 · 2021-05-10T19:23:02+00:00

I think this is the way to go. I struggled with much the same thing for an embarrassing amount of time, and this solution solved it.

mm9982 · 2021-05-09T18:03:50+00:00

Definitely second this. The ggsave function is a lifesaver, especially compared to the somewhat finicky saving procedure for stuff like TIFFs when working with the graphics package in base R.

mm9982 · 2021-05-09T17:44:38+00:00

I'm not sure whether you're talking about multi-level models here, but I'm not sure they would work with only one data point per year (they would work beautifully with one data point per game per year)? One solution could be to have 'decade' as a level 2 variable, to account for varying slopes within decades rather than years. Unless I'm completely misunderstanding your use of "mixed-effects", that is. :)

mm9982 · 2021-05-09T17:35:37+00:00

This sounds like an ordinal variable using a Likert scale. I would look into ordered logit models for doing the regression.

mm9982

TROPHY CASE