Friday links: other people hate you (and that’s ok), R should be optional, RABBITS, and more

Also this week: sleep vs. you, Tony Ives vs. statistical machismo, tips for gender-balancing your seminar series, the origin of deanlets, a rare retraction in ecology, why ecologists and evolutionary biologists give good talks, and more. Lots of good stuff this week!

From Meg:

Improve the gender balance at your conference (or in your department’s seminar series) using these four simple, straightforward tips. One thing they suggest is that it can be helpful to have a list of names of women in a particular field. I have parked the domain for this purpose, but haven’t done anything with it. (I got the idea to park that domain based on Anne’s List, which highlights women neuroscientists.)

I am so glad to read that I’m not the only person who gets anxious when receiving vague email requests to meet. There is no surer way to get my anxiety up than to send an email saying, “Can we chat some time tomorrow?” with no indication of what the email is about. And I don’t just worry if it’s from a boss-like figure. It’s also true when I get a vague email from a collaborator, colleague, or lab member.

I also enjoyed this post by PsycGirl, who has the helpful reminder that people will hate you. This is something that is hard for me (and, based on the twitter discussion, apparently for many others, too), but that I’ve been working on. One thing that I remind myself of is that other people will disagree fundamentally with some of my values (just as I will disagree with theirs). If we didn’t disagree, something would be wrong.

From Jeremy:

Tim Poisot says reviewers shouldn’t enforce R as a standard (or even enforce open source software, he might have added). Tim’s right. And as Ethan White notes in the comments, if you disagree then what you’re really saying is that R shouldn’t exist because everyone should’ve just stuck with adding machines whatever everybody used before adding machines SAS.

A rare retraction in ecology: a high-profile paper in Global Change Biology, which found that plants migrate to lower elevations in response to global warming, has been retracted because of a coding error. The authors were careful about double-checking their results but nevertheless missed the error, which happens. And as soon as the error was discovered, the authors did the right thing and retracted, for which they deserve kudos. So I’m not sure why the reviewer who discovered the error sounds snarky about it. Anybody can make an honest mistake, and it’s bad for both individual scientists and science as a whole to pretend otherwise. More on this from Brian in a forthcoming post.

Tony Ives shows that it’s fine to just log-transform your count data and use least-squares linear models for null hypothesis tests. You only sacrifice a little bit of power vs. a properly-specified generalized linear model or generalized linear mixed model, and your inferences about the null hypothesis will be much more robust to model mis-specification, preventing inflation of the type I error rate. Tony 1, statistical machismo 0. I’m curious if Tony was prompted to write this paper because he ran into reviewers insisting on generalized linear models in a context where transforming the data and then doing least squares was just fine. (ht Meg)

The NSF Biological Sciences directorate has a blog now. (ht Terry McGlynn, via Twitter)

A hypothesis on why your university has so many vice-deans and other administrative layers, and so much red tape. I’ll add my own hypothesis (based on no evidence or even anecdata): faculty don’t like having to do administrative tasks, so ask for more administrative support. Which results in more administrators getting hired. Which then generates more admin work for everyone. And so the cycle repeats. This isn’t a criticism of individual administrators, the large majority of whom are competent and hardworking. It’s a hypothesis about the dynamics of the whole system.

Speaking of why universities are the way they are…How come any list of the top universities in most any western country has about the same rank ordering as it had a century ago? Whereas most of the biggest corporations from a century ago no longer exist? And what are the implications for university management and national higher education policy? Interesting discussion that I’m still mulling over.

Simply Statistics on the curse blessing of dimensionality. That is, why it can actually be useful to have many variables that were measured on only a few subjects.

I’ve always had the impression that EEB folks give pretty good talks on average, because EEB folks know to foreground the big questions and general concepts. So I was interested to read that system biologist Arjun Raj thinks that too many cell/molecular/biochemical talks lack big questions and general concepts.

This is old but I missed it at the time: Here’s a video of Sarah Hird (of Nothing in Biology Makes Sense! fame) giving a hilarious BAHFest talk on why mammals sleep. It’s only 7 minutes, click through! 🙂

Aww, isn’t that a cute bunny rab…OH GOD RUN FOR YOUR LIFE!!!11! 🙂 (ht Marginal Revolution)

And finally: the most 1970s thing you’ll read this week. I give you the US Forest Service on how to make a cocktail. Diagrams and all! Yes, really. 🙂

10 thoughts on “Friday links: other people hate you (and that’s ok), R should be optional, RABBITS, and more

  1. Meg: Start a list as a wiki rather than on WordPress and then many people can easily contribute to it, making your work a lot less. I’d contribute. (It’s a neat idea.)

      • I like this idea! Our WiS (Women in Science) club at Cal State Northridge is teaming up to write pages for historical women in science that have only a few lines or no wiki page at all, so perhaps we can link your page from some of ours!

  2. Just wanted to say that the comments about this retraction over at Retraction Watch are really depressing. I’m fine with what Retraction Watch posts, with rare exceptions. And usually the RW authors are careful to distinguish honest mistakes from dishonest ones. But man, as best I can tell a number of the commenters over there are just looking for an excuse to rip people. I’m sure they wouldn’t admit that, but I suspect that deep down that’s what they enjoy about commenting over there–it’s a forum in which you can rip people and feel good about it, because often the people you’re ripping committed fraud. So when they aren’t provided with an excuse to rip people–as in this case, where competent, careful scientists were unlucky enough to have a mistake slip through and then corrected the record right away when it was discovered–they tie themselves in knots trying to find one.

    I’m sure they think that they’re defending science as a whole from the incompetence and dishonesty of individual scientists. But in fact, they’re actually harming science as a whole by refusing to distinguish honest mistakes by careful scientists from fraud and incompetence.

    • Yes, it’s unreasonable to think that scientists will never make mistakes, even when they are being really careful. So, in my opinion, these authors should be commended for correcting an error once it was found. As you say, attacking people for admitting to honest mistakes definitely harms science. It’s already hard to step forward and admit publicly to a mistake. If doing so leads to attacks, it will only make that even harder (and, therefore, less likely that people will do so.)

  3. I wonder how often papers like Tony’s new one get cited in responses to reviewers, relative to the number of regular citations. I bet it’s pretty high.

    • Well, such papers also get regular citations that preempt reviewers. You cite a paper like Tony’s in the Methods section to justify your methodological choices and so (hopefully) preempt criticism from reviewers.

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