May 1, 2012

We can explain anything

If you have a research finding that is statistically borderline but makes sense biologically, it often seems that the biological explanation should make it more convincing.  Unfortunately, people are really good at explanations and almost any set of flimsy starting materials can be woven together into a superficially firm explanatory facade.  Keith Baggerley, who analyses gene expression data, says that the cancer researchers he works with can always find explanations for a list of genes that are overactive in a particular experiment — and he’s verified this by giving them completely random gene lists.

The Herald has a nice example in an article on functional foods:

You might be surprised to learn that you can often visually identify the function of natural foods. …Walnuts are nicknamed “brain food” and they look just like tiny brains complete with left and right hemispheres.

Sliced tomatoes resemble the structure of the heart with multiple chambers and, you guessed it, are credited with reducing the risk of heart disease. The list goes on – avocados for the uterus, celery for bones. It seems functional foods have always existed if you look closely.

It helps if you are allowed to stretch both the conditions for similarity and for functionality — celery isn’t distinctively good for bones, and the similarity of avocado to the uterus depends enormously on which variety you choose (or perhaps the Reed cultivar, in season now, and the seedless cocktail avocados are supposed to have other functions).     It also helps if you can ignore badly-fitting examples:  a Canadian paper recently had a similarly credulous story about mushrooms as a functional food, but edible mushrooms are of many different shapes, and the common cultivated mushroom shares its shape with things that you really don’t want to eat.

I won’t even comment on what organ the carrot’s shape shows it supposed to benefit.

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Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. He also blogs at Biased and Inefficient See all posts by Thomas Lumley »

Comments

  • avatar
    Simon Moyes

    Rod cells in the eyes for better night vision.

    12 years ago