Using a GRIM method to find unlikely published results

Discovering which published studies may be incorrect or fraudulent takes some work and here is a newer tool: GRIM.

GRIM is the acronym for Granularity-Related Inconsistency of Means, a mathematical method that determines whether an average reported in a scientific paper is consistent with the reported sample size and number of items. Here’s a less-technical answer: GRIM is a B.S. detector. The method is based on the simple insight that only certain averages are possible given certain sets of numbers. So if a researcher reports an average that isn’t possible, given the relevant data, then that researcher either (a) made a mistake or (b) is making things up.

GRIM is the brainchild of Nick Brown and James Heathers, who published a paper last year in Social Psychological and Personality Science explaining the method. Using GRIM, they examined 260 psychology papers that appeared in well-regarded journals and found that, of the ones that provided enough necessary data to check, half contained at least one mathematical inconsistency. One in five had multiple inconsistencies. The majority of those, Brown points out, are “honest errors or slightly sloppy reporting.”…

After spotting the Wansink post, Anaya took the numbers in the papers and — to coin a verb — GRIMMED them. The program found that the four papers based on the Italian buffet data were shot through with impossible math. If GRIM was an actual machine, rather than a humble piece of code, its alarms would have been blaring. “This lights up like a Christmas tree,” Brown said after highlighting on his computer screen the errors Anaya had identified…

Anaya, along with Brown and Tim van der Zee, a graduate student at Leiden University, also in the Netherlands, wrote a paper pointing out the 150 or so GRIM inconsistencies in those four Italian-restaurant papers that Wansink co-authored. They found discrepancies between the papers, even though they’re obviously drawn from the same dataset, and discrepancies within the individual papers. It didn’t look good. They drafted the paper using Twitter direct messages and titled it, memorably, “Statistical heartburn: An attempt to digest four pizza publications from the Cornell Food and Brand Lab.”

I wonder how long it will be before journals employ such methods for submitted manuscripts. Imagine Turnitin for academic studies. Then, what would happen to authors if problems are found?

It also sounds like a program like this could make it easy to do mass analysis of published studies to help answer questions like how many findings are fraudulent.

Perhaps it is too easy to ask whether GRIM has been vetted by outside persons…

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