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110 Science mixes it up with statistics10.2 CollaboratorsGood collaborators make all the difference, both in terms of happiness andproductivity. But how does one find them? Good collaborators, like goodfriends, cannot be found by direct search. They appear when you are pursuingmutual interests. I’ve been lucky to collaborate with many great statisticalcolleagues, post docs and graduate students. Here I’ll focus on scientific collaborators,because such bonds are not likely to happen by chance. To gainentrance into good scientific collaborations requires a substantial investmentof time and effort. In some cases, even when you are an established researcheryou have to work for several years as part of the research team before youget regular access to the leading scientist on a project. I have spent manyan hour talking with brilliant graduate students and post docs working forleading researchers. This is a great way to participate in big science projects.I find that if I provide them with statistical insights and guidance, they willhelp me with the data. Sharing expertise and effort in this way is productiveand fun.Asuccessfulappliedprojectrequiresgooddataandtypicallyastatisticiancannot produce data on her own. Invariably, scientists have invested years oftheir lives to procure the data to which we want to gain access. Hence, itis traditional for the lab director to be last author, a position of honor, onany papers involving the initial publication of these data. In addition, typicallya post doc or graduate student who has also played a substantial rolein getting the data is the first author of such papers. Because these dataare presented to us electronically, it is easy to forget the tremendous investmentothers have made. We too want to have a leading role for the statisticsteam, and the authorship rules can be frustrating. But I have found that itis immensely worthwhile to participate in such projects and contribute wherepossible. Having made such an investment, it is usually possible to do moreinvolved statistical analysis in a follow-up paper. Naturally, this is where thestatisticians get key authorship roles.Collaboration requires a tremendous amount of sharing and trust, so it isnot surprising that it can be challenging to succeed. Just as good collaborationsbuoy our spirits, bad collaborations wear us down. My mother never wentto college, but she was fond of the maxims of economics: “Time is money” and“Don’t throw good money after bad” were her favorites. Both of these shedlight on the dilemma of what to do about a bad collaboration. None of us likesto invest a lot of effort and get nothing in return, and yet, an unsatisfyingor unhappy collaboration does not ultimately lead to good research. I havehad many experiences where I’ve walked away from a project after makingsubstantial investments of effort. I have never regretted getting out of suchprojects. This leaves more time for other great collaborations.