Applied Statistics

Sanjay Srivastava writes:

Below are the names of some psychological disorders. For each one, choose one of the following:

A. This is under formal consideration to be included as a new disorder in the DSM-5.

B. Somebody out there has suggested that this should be a disorder, but it is not part of the current proposal.

C. I [Srivastava] made it up.

Answers will be posted in the comments section.

1. Factitious dietary disorder – producing, feigning, or exaggerating dietary restrictions to gain attention or manipulate others

2. Skin picking disorder – recurrent skin picking resulting in skin lesions

3. Olfactory reference syndrome – preoccupation with the belief that one emits a foul or offensive body odor, which is not perceived by others

4. Solastalgia – psychological or existential stress caused by environmental changes like global warming

5. Hypereudaimonia – recurrent happiness and success that interferes with interpersonal functioning

6. Premenstrual dysphoric disorder – disabling irritability before and during menstruation

7. Internet addiction disorder – compulsive overuse of computers that interferes with daily life

8. Sudden wealth syndrome – anxiety or panic following the sudden acquisition of large amounts of wealth

9. Kleine Levin syndrome – recurrent episodes of sleeping 11+ hours a day accompanied by feelings of unreality or confusion

10. Quotation syndrome – following brain injury, speech becomes limited to the recitation of quotes from movies, books, TV, etc.

11. Infracaninophilia – compulsively supporting individuals or teams perceived as likely to lose competitions

12. Acquired situational narcissism – narcissism that results from being a celebrity

In academic research, “sudden wealth syndrome” describes the feeling right after you’ve received a big grant, and you suddenly realize you have a lot of work to do. As a blogger, I can also relate to #7 above.

. . . and statisticians

It’s easy to make fun of psychiatrists for this sort of thing–but if statisticians had a similar official manual (not a ridiculous scenario, given that the S in DSM stands for Statistical), it would be equally ridiculous, I’m sure.

Sometimes this comes up when I hear about what is covered in graduate education in statistics and biostatistics–a view of data analysis in which each different data structure gets its own obscurely named “test” (Wilcoxon, McNemar, etc.). The implication, I fear, is that the practicing statistician is like a psychiatrist, listening to the client, diagnosing his or her problems, and then prescribing the appropriate pill (or, perhaps, endless Gibbs sampling^H^H^H^H^H^H^H^H^H^H^H^H^H^H^H talk therapy). I don’t know if I have a better model for the training of thousands of statisticians, nor maybe do I have a full understanding of what statistical practice is like for people on the inferential assembly line, as it were. But I strongly feel that the testing approach–and, more generally, the approach of picking your method based on the data structure–is bad statistics. So I’m pretty sure I’d find much to mock in any DSM-of-statistics that might be created.

Another uncomfortable analogy between the two professions is that statistical tests, like psychiatric diagnoses, are trendy, despite their supposed firm foundation in mathematics and demonstrated practical success (just as psychiatry boasts a firm foundation medicine along with millions of satisfied customers over the decades). Compounding the discomfort is that some of the oldest and most established statistical tests are often useless or even counterproductive. (Consider the chi-squared test, which when used well can be helpful–see chapter 2 of ARM for an example–but is also notorious as being nothing more than “a test of sample size” and has let many researchers to disastrously oversimplify their data structures in order to fit the crudest version of this analysis.)

Instead of a DSM, the statistical profession has various standard textbooks, from Snedecor and Cochran to . . . whatever. But our informal DSM, as defined by practice, word-of-mouth, and our graduate curricula, is nothing to be proud of.

Comments

  1. #1 John
    March 12, 2010

    Widespread licensing or certification of statisticians would further ossify the kinds of practices you’re criticizing.

  2. #2 Donna B.
    March 13, 2010

    I volunteer for clinical trials testing #8, and I have some ideas for treatments.

  3. #3 mort_fin
    March 13, 2010

    most of Chicago’s north side suffers from #11

  4. #4 Bill Drissel
    March 26, 2010

    Why is there no Statistician General?

  5. #5 Alexander Ploner
    July 2, 2010

    This may be a stupid question, but what is wrong with picking methods based on the structure of my data? Assuming that it is a well designed study/experiment, the structure may reflect the design, the data collection and/or inherent relationships between variables, things that IMO should have an effect on my choice of method. IME, the most brutal abuse of statistical methodology happens when someone applies the same hammer to daffodils, small cuddly animals, large person-eating animals, stamps, and the occasional small nail (metaphorically speaking, of course).

  6. #6 Andrew Gelman
    July 4, 2010

    Alexander: When I referred to “data structure,” I wasn’t talking about the distinctions between daffodils, animals, and nails, but rather about the distinction between count data, survival data, etc. Training for statisticians and especially for biostatisticians is often focused on having a different method for each data structure, ignoring the substance of the problem. And then you get people doing things like discretizing their data so they can do chi-squared tests.

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