Stargazer is the single greatest R package I’ve discovered this year (although I think it was the most excellent Jos Elkink who first pointed me to it). stargazer() can turn objects created by many, many R commands into nicely formatted LaTex code. A glorious time saver that I use with only a slight, but very important, tweak:
stargazer(model.object, digits=2, star.cutoffs=c(.05,.01,.001))
So, in sum, if you ever meet Marek Hlavac while at Harvard buy him a drink for me.
Useful blog post at orgtheory.net. It consists of a series of pointers from editors at top sociology journals as to what makes for useful comments/review notes when you are asked to review an academic article.
As we in academia have to do this quite a bit, even if just informally helping out a colleague, these are some useful tips to keep in mind. A few that stuck out for me:
“Be developmental – Good reviews suggest solutions to the problems raised. Just saying, “this is bad, this is wrong, I disagree with this, why should I care…” doesn’t really help the authors. Telling them what would solve the problem for you does. If you can’t come up with a tractable solution, you may want to reconsider whether or not you are making a valid criticism, or being too negative and nit-picky. All research has weaknesses. The question is, are these weaknesses fatal, addressable, or just inherent to the theory or methodological approach employed and thus not something the author can address but should be mindful of when drawing inferences and making claims.”
“Start from a happy place – If you approach a review assuming you are going to reject the manuscript odds are you will, because you will focus primarily on information that confirms this expectation. As a reviewer, when I start reading a paper I assume that I’m going to give it an R&R unless the authors convince me otherwise. This approach makes me more open to the positive aspects of the paper and the potential nuggets that can be developed, and which might be overlooked if you are only looking for reasons to reject the manuscript. It may not take long for the authors to convince me to reject their paper, but I’ve also seen some real diamonds in the rough polished into gems because I was open to seeing what the paper might be.”
Let me add my voice to the chorus out there praising the new R GUI, RStudio. It’s swell, and should help new users get to grips with the steep learning curve much quicker. I especially like the fact that it is multi-platform, allows graphics to stack rather than be overwritten and has that nice summary window for visualizing the data you have loaded.
As for me, emacs (plus ESS) remains my tool of choice.
As an add-on to the previous discussion, the New York Times has posted an article discussing the expanded use of interactive “clickers” in lecture halls as a tool for engaging undergraduates. Now we just need the cost to come way down or to develop an Android/iphone app that provides the same functionality.
With a hat tip to Ken Benoit’s blog, This xtranormal.com video should answer any questions you have about the pursuit of a PhD in political science. The truth is painful and wickedly funny.
So you want to get a PhD in political science…
Yale University offers a series of their courses online through their Open Yale Courses program (videos of lectures, notes, etc.), and the game theory course with Ben Polak is quite good. It’s a nice resource for refreshing one’s memory (or starting from scratch if so needed).
Update: I posted this in a hurry yesterday as I wanted to share the link with colleagues. Let me just add that of the lectures I’ve viewed online, Ben Polak deserves credit for being an excellent lecturer. He’s charismatic (which is always nice) and has some nice tricks for conveying the subject to students (much class participation). On the technical side, the video and sound quality is excellent.
In sum, I would be completely comfortable directing someone, even those completely unfamiliar with game theory and afraid of formal models, to these videos confident that they will get something valuable out of them.
With a hat tip to the Revolutions blog, a FREE introductory book to statistics and probability which illustrates all of its examples in R has been released (free pdf version and pay-for paperback version).
I’ve only skimmed through the first 80 or so pages but must say it looks like a very nicely written introduction to probability, statistics and R itself. This might be a good resource for those teaching Quants I courses.