Editor’s note: Simply Statistics is still freaking out about the government shut down and potential impending economic catastrophe if the debt ceiling isn’t raised. Since anything new we might write seems trivial compared to what is going on in Washington, we are reposting an awesome old piece by Roger on finding good collaborators.
The job of the statistician is almost entirely about collaboration. Sure, there’s theoretical work that we can do by ourselves, but most of the impact that we have on science comes from our work with scientists in other fields. Collaboration is also what makes the field of statistics so much fun.
So one question I get a lot from people is “how do you find good collaborations”? Or, put another way, how do you find good collaborators? It turns out this distinction is more important than it might seem.
My approach to developing collaborations has evolved over time and I consider myself fairly lucky to have developed a few very productive and very enjoyable collaborations. These days my strategy for finding good collaborations is to look for good collaborators. I personally find it important to work with people that I like as well as respect as scientists, because a good collaboration is going to involve a lot of personal interaction. A place like Johns Hopkins has no shortage of very intelligent and very productive researchers that are doing interesting things, but that doesn’t mean you want to work with all of them.
Here’s what I’ve been telling people lately about finding collaborations, which is a mish-mash of a lot of advice I’ve gotten over the years.
- Find people you can work with. I sometimes see situations where a statistician will want to work with someone because he/she is working on an important problem. Of course, you want to be working on a problem that interests you, but it’s only partly about the specific project. It’s very much about the person. If you can’t develop a strong working relationship with a collaborator, both sides will suffer. If you don’t feel comfortable asking (stupid) questions, pointing out problems, or making suggestions, then chances are the science won’t be as good as it could be.
- It’s going to take some time. I sometimes half-jokingly tell people that good collaborations are what you’re left with after getting rid of all your bad ones. Part of the reasoning here is that you actually may not know what kinds of people you are most comfortable working with. So it takes time and a series of interactions to learn these things about yourself and to see what works and doesn’t work. Of course, you can’t take forever, particularly in academic settings where the tenure clock might be ticking, but you also can’t rush things either. One rule I heard once was that a collaboration is worth doing if it will likely end up with a published paper. That’s a decent rule of thumb, but see my next comment.
- It’s going to take some time. Developing good collaborations will usually take some time, even if you’ve found the right person. You might need to learn the science, get up to speed on the latest methods/techniques, learn the jargon, etc. So it might be a while before you can start having intelligent conversations about the subject matter. Then it takes time to understand how the key scientific questions translate to statistical problems. Then it takes time to figure out how to develop new methods to address these statistical problems. So a good collaboration is a serious long-term investment which has some risk of not working out. There may not be a lot of papers initially, but the idea is to make the early investment so that truly excellent papers can be published later.
- Work with people who are getting things done. Nothing is more frustrating than collaborating on a project with someone who isn’t that interested in bringing it to a close (i.e. a published paper, completed software package). Sometimes there isn’t a strong incentive for the collaborator to finish (i.e she/he is already tenured) and other times things just fall by the wayside. So finding a collaborator who is continuously getting things done is key. One way to determine this is to check out their CV. Is there a steady stream of productivity? Papers in good journals? Software used by lots of other people? Grants? Web site that’s not in total disrepair?
- You’re not like everyone else. One thing that surprised me was discovering that just because someone you know works well with a specific person doesn’t mean that _you_ will work well with that person. This sounds obvious in retrospect, but there were a few situations where a collaborator was recommended to me by a source that I trusted completely, and yet the collaboration didn’t work out. The bottom line is to trust your mentors and friends, but realize that differences in personality and scientific interests may determine a different set of collaborators with whom you work well.
These are just a few of my thoughts on finding good collaborators. I’d be interested in hearing others’ thoughts and experiences along these lines.
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