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As a biologist, many of the research projects I work on at some point involve collaboration with a statistician, whether it be for simple advice or for implementing and testing a model for my data. My statistics colleagues admit that they do a significant amount of collaboration, insomuch that the tenure review process only considers papers on which they are the first or last author.

What would make me (or any other scientist) a better collaborator? What would make it easier for you (as a statistician) to work with me? Specifically, what is one statistics concept you wish all of your scientist collaborators already understood?

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    $\begingroup$ This sounds like CW material. $\endgroup$
    – whuber ♦
    Dec 17, 2010 at 22:57
  • $\begingroup$ Clear objective of the study is very important for collaboration. $\endgroup$
    – user158565
    May 16, 2019 at 1:32

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My answer is from the point of view of an UK academic statistician. In particular, as an academic that gets judged on advances in statistical methodology.

What would make me (or any other scientist) a better collaborator?

To be blunt - money. My time isn't free and I (as an academic) don't get employed to carry out standard statistical analysis. Even being first/last author on a paper that uses standard methodology is worth very little to me (in terms promotion and my personal research). Paying for my time will buy me out of administrative or teaching duties. Payment could be through a joint grant.

In the UK, every five or so years academics have to submit their four best papers. My papers are judged on their contribution to the statistical literature. It sucks, but that's the way it is.

Now it may well be that you have a very interesting problem which would lead to advances in statistical techniques. However, just think about the size of your statistics department compared to the rest of the Uni. There probably won't be enough statisticians to go around.

In saying that, I do try and do some "statistical consultancy" once a year to broaden my interests and to help for teaching purposes. This year I did some survival analysis. However, I've never advertised this fact and I still get half dozen requests each year for help!

Sorry for being so negative :(

Specifically, what is one statistics concept you wish all of your scientist collaborators already understood?

That statisticians do statistical research. As one of my collaborators said:

Surely there's nothing left to solve in statistics?

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    $\begingroup$ I'd just like to reinforce the point about the money (for projects where there is little novelty in the statistics)! The other point I'd make is that for projects that do advance the statistics, make sure you put as much effort into helping your collaborator in publishing his paper in stats journals that you would want from him in publishing the primary result in a biology journal. I know from painfull experience that this does not always happen - I have had a couple of projects where the stats paper went unpublished as my collaborator lost interest :-( $\endgroup$
    – Dikran Marsupial
    Dec 17, 2010 at 15:55
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I think the concept that few scientists grasp is this: A statistical result can really only be taken at face value when the statistical methods were chosen in advance while the experiment was being planned (or while preliminary data were collected to polish methods).

You are likely to be mislead if you first analyze the data this way, then that way, then try something else, then analyze only a subset of data, then analyze only that subset after removing an obvious outlier..... and only stop when the results match your preconceptions or has lot of asterisks. That is a fine way to generate an hypothesis, but not an appropriate way to test one.

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    $\begingroup$ Who was it that said "calling a statistician after an experiment has been completed is like calling a doctor for an autopsy" or something like that? $\endgroup$
    – cespinoza
    Dec 18, 2010 at 8:48
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    $\begingroup$ @cespinoza : Ronald Fisher : To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. $\endgroup$
    – Joris Meys
    Dec 18, 2010 at 19:36
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    $\begingroup$ +1 apart from money, the first and foremost thing I want a researcher to bring me is a hypothesis! and not -again- some garbled dataset and the question : can you get something out of this? Yes I can. No, it won't mean a bloody damn thing. $\endgroup$
    – Joris Meys
    Dec 18, 2010 at 19:37
  • $\begingroup$ People may tend to err on the side of unpreparedness. Yet a world in which inquiry were driven only by hypotheses, with no room for exploration, would be a dreary one. $\endgroup$
    – rolando2
    Feb 6, 2013 at 1:48
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To get a good answer, you must write a good question. Answering a statistics question without context is like boxing blindfolded. You might knock your opponent out, or you might break your hand on the ring post.

What goes into a good question?

  1. Tell us the PROBLEM you are trying to solve. That is, the substantive problem, not the statistical aspects.

  2. Tell us what math and statistics you know. If you’ve had one course in Introductory Stat, then it won’t make sense for us to give you an answer full of mixed model theory and matrix algebra. On the other hand, if you’ve got several courses or lots of experience, then we can assume you know some basics.

  3. Tell us what data you have, where it came from, what is missing, how many variables, what are the Dependent Variables (DVs) and Independent Variables (IVs) – if any, and anything else we need to know about the data. Also tell us which (if any) statistical software you use.

  4. Are you thinking of hiring a consultant, or do you just want pointers in some direction?

  5. THEN, and ONLY THEN tell us what you’ve tried, why you aren’t happy, and so on.

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    $\begingroup$ +1 Great advice, especially #1. Concerning #2, be careful not to overestimate what your potential client might know! (I must have had hundreds of professional conversations in which the client said "I took x statistics courses in graduate school but have forgotten everything"; x typically is 3 or 4 and the clients were anywhere from zero to 40 years out of school.) $\endgroup$
    – whuber ♦
    Dec 18, 2010 at 21:21
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Having no preconceived ideas about the method you should use solely based on papers. Their ideas, logic or methods may be faulty. You want to think about your problem and use the most appropriate set of tools. This reminds me of reproducing cited information without checking the source.

On the other hand, paper with methods (or logic) that differs from the rest of literature may hinder or cull a review process because "it's not the norm".

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