Feb

23

Last week, I mentioned that successful consultants have five categories of skills; communication, testing, statistics, programming and generalist.

COMMUNICATION

Communication is the number one most important skill. All five are necessary to some extent, but a terrific communicator with mediocre statistical analysis skills will get more business than a stellar statistician that can’t communicate. Communication is a lot more than explaining results to clients or making small talk at meet ups.

Documentation

Communication includes documentation, both in your code and internal documents such as codebooks or an internal wiki. It includes letting clients know what you’re going to do, what it’s going to cost, what that cost includes, what were your results and what those results mean. If you’re good at communicating with clients, colleagues and your future self, you’re half-way to success.

An example of the critical nature of communication can be found in the following retraction:

The identified programming error was in a file used for preparation of the analytic data sets for statistical analysis and occurred while the variable referring to the study “arm” (ie, group) assignment was recoded. The purpose of the recoding was to change the randomization assignment variable format of “1, 2” to a binary format of “0, 1.” However, the assignment was made incorrectly and resulted in a reversed coding of the study groups.”

Aboumatar and Wise (2019, p. 1417)

Because of this incorrect coding, the reported results were the exact opposite of what actually occurred.

Document coding!

Here is an example from a current research project where the CES-D depression scale was used, which requires several items to be reverse-coded before scoring.

In the HTML file where the user enters data that’s written to the database there is this comment:

    <h5 >I felt that I was just as good as other kids.</h5>
    <! –– This is reverse-coded. Don’t you dare change it. ––>
<div class=”row mb-3″>
    <button id=”cesd4_1″ data-src=”3″ class=”cesd4 btn btn-light shadow-box col-5 my-3 mx-auto”>Not at all</button>

 In the original file to read in the data to SAS, there is a comment:

*** NOTE: CESD IS ALREADY REVERSE-CODED. DOES NOT NEED CODING!;

FILENAME REFFILE2 ‘/home/directory3/data_analysis_examples/crossroads/cesd.xlsx’;

In the internal wiki, there is this note:

Tables in Acme Project Database

CESD – Center for Epidemiologic Studies Depression Scale – NOTE: The data are reverse coded at data entry. There is no need to reverse code these. There are 25 columns in this table; ID, username, session number, questions 1 through 20 of the CESD scale, the CESD total which is the sum of the 20 questions, named item21 for some odd reason, and a time stamp.

Document everything! Document how are items coded, how subscales or totals are computed.

This may seem like overkill, but how many retractions could be prevented by this level of documentation? If you are a consultant, it’s probable that at some point someone else will be looking at these data, or that you may be called back a year later to do a longitudinal analysis. Your colleagues and future you will thank you. A year or two from now, I don’t want to be looking at this data set and wondering if I need to reverse-code those items or if it was already done. I want to KNOW!

I deeply suspect that there are more erroneous results published due to incorrect coding of data than to incorrect analyses. After all, the peer reviewers, editors and readers see how you analyzed your data. No one sees how you coded it but you and, possibly, the person who has your position after you.

Feb

17

A few weeks ago, I ended my post with “there is one thing a statistical consultant absolutely must have and promised to say what that is in the next post. Maria and I had just picked up our rental car at the Detroit airport when she turned to me and asked:

So, what is the one thing a statistical consultant has to have?

I told her,

“I have absolutely no idea what I was thinking last month!”

In my defense, I have been in five states and 22 cities in the past 21 days. Maria says it is only 16 because I was in Minneapolis, Fargo and Denver twice each. She also says I can’t count Denver, Chicago or San Francisco since I only changed planes there. Poo!

In Long Beach thinking about statistical consultants

Now that I am back in Los Angeles and my brain has unfrozen I think there are actually five things you must have but one of these is the most important. In my not at all humble opinion, though, you need ALL FIVE.

The actually five skills a statistical consultant must have

Man playing drum in preparation for me saying what are the 4 skills statistical consultants must have
Drum roll, please
  1. COMMUNICATION – This is the number one most important skill. If you don’t have the rest, you’ll still suck and be unemployed but a terrific communicator with mediocre statistical analysis skills will get more business. I don’t just mean shaking hands and small talk at conferences, either. Communication includes documentation, both in your code and in codebooks, an internal wiki, etc. It includes letting clients know what you’re going to do, what it’s going to cost, what that cost includes, what were your result and what those results mean. If you’re good at communicating with clients, colleagues and your future self, you’re half-way to success.
  2. TESTING – I’ve ranted on this blog a lot about testing because it is one of the areas where people often seem to fall short early in their careers. I got a lot of hate for this post when I said I don’t hire self-taught developers because there are things they don’t teach themselves adequately, like testing.
  3. Statistics – Well, duh. Props to the person in the Chronicle of Higher Education forum whose signature read, “Being able to find SPSS in the start menu does not qualify you to run a multinomial logistic regression.” Your clients may not know what power, quasi-complete separation or multicollinearity mean in interpreting an analysis. They do trust that you understand whatever is necessary to be understood for the work. Don’t let them down.
  4. Programming – when I was a graduate student Very Important Professors had lowly peon graduate students and programmers to write their code for them. All of those people had started their careers using punched cards, (honest!) it was that long ago. All of the statistical consultants I know do programming, or can code their own analyses if necessary. Even if you aren’t doing it all yourself – I’m certainly not these days – you need to know enough to review the code your minions wrote or help said minions when they get stuck. Sometimes, it’s just quicker to do it by yourself than explain to someone else, especially if you need to fix a bug in a code that a client is waiting on.
  5. Be a generalist – I’ll have more to say about this in future posts. In brief, even the consultants I know who are well-known specialists in one language know and use others. If you think your career is going to be you sitting on a mountain or in penthouse office, pontificating to others about sums of squares, the computation of Wilks’ lambda or options for PROC GLMSELECT , you are going to be sadly disappointed. On the other hand, if you do know of a job like that, I would consider taking it for a sufficiently large quantity of money.

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