Let’s Ask the Expert

The research team has a new statistician; not a new analyst, but new statistician. If you look at it as a pecking order, the statistician oversees the analyst. Our former statistician retired recently, leaving the team to find a replacement. The University has a relatively new Quantitative Health Sciences Department and many of the services once procured through individual department statisticians are now going through QHS. Or at least this is how I think it’s going. These are things that I don’t necessarily need to know and as I have plenty of things occupying my “need to know” gray matter right now, I can just follow along here.

The significance of the new team member, to me, was that it generated the need for a meeting so that he could be brought up to speed on the project. This meeting happened this afternoon. I believe it was good for him (as well as the Chair of the Quantitative Methods Core, his boss, also in attendance). I know that it was good for me. I’ve now heard the project and its various aspects described on a number of occasions, and each time gain some new insight. Today, that insight was that I have a pretty good grasp on where the data for this study comes from, the different sources that generate it, how it’s stored, where it’s stored, who’s managing it, and so forth. I also had a pretty clear understanding of where the problem spots and/or issues with it are (mostly gone over, yet again, in today’s morning meeting).

I decided to pay close attention during the meeting on the questions that the statistician asked. I imagine that these are the kinds of questions that an informationist, embedded librarian, or anyone concerned with data management and planning would ask a research team. Here are some that I noted. If you’re doing an interview with a researcher about his/her data, are you asking these questions?

• Is the data in one place or multiple places? 
• Do the different sources merge together easily?
• Are the variable names consistent across the sources?
• Where is the merged data stored and how?
• When and/or how often do you do data pulls from the sources?

Additionally, the statistician said that he wanted to be walked through the process. He wanted to generate a visual for himself of how everything works together. I found this request confirmation of much of what I’ve been reading and thinking about in terms of how we best see, understand, and communicate systems and processes. Visuals are important. I remember meeting with one of the chief programmers a few months back and how helpful it was when he pulled out a marker and drew us a picture on the whiteboard to explain all of this.*

*NOTE: If you’re interested in the art of explanation, check out The Art of Explanation by Common Craft founder, Lee Lefever. I’m pretty sure I mentioned this a few posts back, but in case you missed it… Also, Common Craft has made wonderful templates of their cut-out characters available for free to download and use in your own creations. Give it a try and see how well you do at explaining a concept or problem. Make a little video and share it with me.

So, if you’re keeping up with the process of the research study, the next step for the statistician is to collect data from the first cohort and start to play with it; see what it shows so far; see if it identifies any gaps of missing data and/or holes in the process that need to be addressed. It’ll be a couple of months, at least, before we hear back, but it was obvious that the team was excited about this move.

A few questions that I’m left with, following today, are:

• What’s the difference between an analyst and a statistician?
• What is my role, if any, in this aspect of the study?

One last interesting aside – When we went around the table to introduce ourselves and I said, “I’m from the library, serving as the informationist,” Dr. Barton, the Director of the Quantitative Methods Core said, “Oh, good.” I’m the only one who got an “Oh, good.” I’ve no idea what he meant by it, but I like to see it as a positive sign that my library is engaged in this kind of work. Regardless, it was a nice gesture.

Tags: analyst, data management, research team, statistician, statistics