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GidMK's profile
Health Nerd
Health Nerd
Health Nerd
Verified account
@GidMK

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Health NerdVerified account

@GidMK

Epidemiologist. Writer (Guardian, Observer etc). "Well known research trouble-maker". PhDing at @UoW Host of @senscipod Email gidmk.healthnerd@gmail.com he/him

Sydney, New South Wales
theguardian.com/profile/gideon…
Joined November 2015

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    1. Health Nerd‏Verified account @GidMK 5 Aug 2020

      Because the game was random, you can use the reported numbers to compare to the numbers you'd get if people reported the colours accurately, and determine whether they were probably lying

      2 replies 2 retweets 18 likes
      Show this thread
    2. Health Nerd‏Verified account @GidMK 5 Aug 2020

      Here's the main finding in graphical form. If you look at the columns on the right, they are higher than the ones on the left, so obese people lie more! Except, there's something a little weird here. The statistical tests don't actually compare obese and lean peoplepic.twitter.com/805NZQfBTF

      2 replies 4 retweets 42 likes
      Show this thread
    3. Health Nerd‏Verified account @GidMK 5 Aug 2020

      If you look carefully, all of these statistical tests are comparing within-group differences - i.e. how likely it is that within the obese/fasted group the results would've been observed due to chance

      1 reply 2 retweets 32 likes
      Show this thread
    4. Health Nerd‏Verified account @GidMK 5 Aug 2020

      But they AREN'T comparing obese and lean people! What you expect to see, going by the abstract and discussion of the study, is a statistical test comparing the proportions BETWEEN groups i.e. comparing obese with leanpic.twitter.com/TA01sdeBfj

      1 reply 2 retweets 32 likes
      Show this thread
    5. Health Nerd‏Verified account @GidMK 5 Aug 2020

      Fortunately, the authors did this analysis as well! You can find it in table 4 of the supplementary materials 🤦‍♂️ What do we see?

      1 reply 2 retweets 23 likes
      Show this thread
    6. Health Nerd‏Verified account @GidMK 5 Aug 2020

      Well, here's the table. The bottom two rows are the interesting ones NO significant differences between reported proportions for pretty much any subgroup of lean vs obese peoplepic.twitter.com/BgYhKLu0J3

      2 replies 9 retweets 73 likes
      Show this thread
    7. Health Nerd‏Verified account @GidMK 5 Aug 2020

      In fact, it appears as if the main finding of this paper completely contradicts the results of this analysis. There does not appear to be any statistically significant differences in the reported values when comparing lean and obese people at all!

      3 replies 11 retweets 98 likes
      Show this thread
    8. Health Nerd‏Verified account @GidMK 5 Aug 2020

      Now, that's pretty bad. But it gets worse This study was probably not designed to test the question of obese vs lean How do we know? Look at the sample size calculationpic.twitter.com/NtOj1k7zwi

      4 replies 2 retweets 34 likes
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    9. Health Nerd‏Verified account @GidMK 5 Aug 2020

      So, they've computed their sample size based on the idea that they want to detect an effect size of 0.25 between two groups But...they didn't include any indication of obese vs lean here. The eventual sample size (150) shows us that

      2 replies 3 retweets 30 likes
      Show this thread
    10. Health Nerd‏Verified account @GidMK 5 Aug 2020

      Instead, it seems almost certain that the original study just looked at lying in fasted vs breakfasted people We can actually see this even more clearly because they ran 36 people through the entire procedure only to exclude them after the fact!pic.twitter.com/YcaJhAfNFh

      1 reply 4 retweets 51 likes
      Show this thread
      Health Nerd‏Verified account @GidMK 5 Aug 2020

      This starts to get a bit murky, because I cannot find a pre-registration for the study That's worrying, because changing your hypothesis after running a study is a classic sign of p-hacking

      6:05 PM - 5 Aug 2020
      • 3 Retweets
      • 82 Likes
      • Gabriela Cuello Dr Chiara Herzog Dr Bex Nicole Marie Roms | 🏳️‍🌈 Humphrey Yogart Dr. Clare Conry-Murray Soumillion Lab Stanzi le Roux
      2 replies 3 retweets 82 likes
        1. New conversation
        2. Health Nerd‏Verified account @GidMK 5 Aug 2020

          Another sign is the statistical analysis. I count upwards of 100 comparisons (Fisher's exact test, chi squared etc) with no correction for multiple comparisons That's...worrying

          1 reply 3 retweets 52 likes
          Show this thread
        3. Health Nerd‏Verified account @GidMK 5 Aug 2020

          If you apply a Bonferroni correction to the results, pretty much every statistically significant finding completely disappears, which is not surprising given that they ran SO MANY tests

          1 reply 2 retweets 44 likes
          Show this thread
        4. Health Nerd‏Verified account @GidMK 5 Aug 2020

          Bringing it back home, we have this sentence in the discussion According to supplementary table 4, this simply isn't true!pic.twitter.com/zNm5GfENI8

          1 reply 4 retweets 33 likes
          Show this thread
        5. Health Nerd‏Verified account @GidMK 5 Aug 2020

          Obese people had differences in behaviour, but the statistical comparisons DIDN'T SHOW A SIGNIFICANT DIFFERENCE Pretty major issue, that

          1 reply 3 retweets 54 likes
          Show this thread
        6. Health Nerd‏Verified account @GidMK 5 Aug 2020

          Anyway, the paper is abhorrent regardless, but I think it also shows some worrying signs of being constructed after the fact from a dataset of a trial with different aims

          1 reply 5 retweets 63 likes
          Show this thread
        7. Health Nerd‏Verified account @GidMK 5 Aug 2020

          Oh, another issue - the paper makes an inherently misleading claim about causality. The primary findings were of a subgroup analysis of non-randomized groups (lean vs obese) and so it's not clear whether this was causal anyway

          1 reply 2 retweets 37 likes
          Show this thread
        8. Health Nerd‏Verified account @GidMK 5 Aug 2020

          Because the randomization was simply fasted vs breakfast, the causal attribution for this study should be comparing those two groups, not the subgroups of obese vs lean

          6 replies 3 retweets 59 likes
          Show this thread
        9. End of conversation
        1. Max Primbs‏ @MaxPrimbs 7 Aug 2020
          Replying to @GidMK

          A small correction here: That's not p-hacking, it's hypothesizing after results are known (HARKing). Both are questionable research practices though.

          0 replies 0 retweets 0 likes
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