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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 26 May 2019

      Having seen this plot, are you more or less confident in the statement that IBS is associated with pet ownership?

      2 replies 0 retweets 2 likes
      Show this thread
    2. Health Nerd‏Verified account @GidMK 26 May 2019

      See, the thing is, that top study appears to be contributing the ENTIRE association. Every other study found no result at all, but one single study has caused the entire relationship to become statistically significantpic.twitter.com/pcW30Bzkhm

      1 reply 0 retweets 2 likes
      Show this thread
    3. Health Nerd‏Verified account @GidMK 26 May 2019

      Being the nerd I am, I decided to rerun the meta analysis on their sample using the metan command in Stata This is a bit quick and dirty, but using a random-effects model with an inverse variance, I get these resultspic.twitter.com/s95D5VYPQ7

      2 replies 0 retweets 2 likes
      Show this thread
    4. Health Nerd‏Verified account @GidMK 26 May 2019

      For the epi nerds, when I run it with a fixed-effects model my results are the same as those reported in the paper, but my random-effects model CI crosses 0 🤔

      2 replies 0 retweets 5 likes
      Show this thread
    5. Sir Panda (Zad Rafi)‏ @dailyzad 26 May 2019
      Replying to @GidMK

      what method did the paper use? fixed-effects (common-effects) seems rarely appropriate for most situations

      1 reply 0 retweets 1 like
    6. Health Nerd‏Verified account @GidMK 26 May 2019
      Replying to @dailyzad

      That's the thing - they report using a random effects model, but I can't replicate that in Stata. I'd probably need to see their code to get the precise effect estimate they generatedpic.twitter.com/2fH3xll8Tc

      1 reply 0 retweets 0 likes
    7. Health Nerd‏Verified account @GidMK 26 May 2019
      Replying to @GidMK @dailyzad

      (I'm also using the DerSimonian and Laird variance estimation, but my guess is that the procedure in Stata produces very slightly different results than other statistical software)

      1 reply 0 retweets 0 likes
    8. Sir Panda (Zad Rafi)‏ @dailyzad 26 May 2019
      Replying to @GidMK

      Hmm interesting. I don't think they actually used the DL method... I calculated the standard errors by taking the natural logs ln(UL/LL) and tried to reproduce it with *metan logOR logSE, fixed eform* I got much wider interval estimates (as expected with random effects)pic.twitter.com/y7kXtgU7YU

      2 replies 0 retweets 0 likes
    9. Sir Panda (Zad Rafi)‏ @dailyzad 26 May 2019
      Replying to @dailyzad @GidMK

      I got the reported results with *metan logOR logSE, fixed eform*. Double checked on R with metafor and got similar results. Any case... I don't think it actually matters whether the interval includes the null or not. All of included studies are regarding nonrandom exposurespic.twitter.com/Ng2PJYtv9A

      2 replies 0 retweets 1 like
    10. Health Nerd‏Verified account @GidMK 26 May 2019
      Replying to @dailyzad

      Yes I saw exactly the same. I reckon they misreported the model they used in the abstract I do agree about the nonrandom exposures, but I think it's worth noting that, done properly, even their own analysis doesn't show an effect

      1 reply 0 retweets 0 likes
      Health Nerd‏Verified account @GidMK 26 May 2019
      Replying to @GidMK @dailyzad

      Also, it's really not ideal practice to not at least do a sensitivity analysis excluding the single study that's driving the entire effect, but to be fair that's what I'd expect from a conference abstract which is why this shouldn't have been a news story in the first place!

      7:57 PM - 26 May 2019
      • 1 Like
      • Sir Panda (Zad Rafi)
      1 reply 0 retweets 1 like
        1. New conversation
        2. Health Nerd‏Verified account @GidMK 26 May 2019
          Replying to @GidMK @dailyzad

          Just noticed if you exclude that study the I^2 drops from 27% to 0% so I reckon there's definitely a rationale for using the sensitivity analysis as the most robust estimate

          1 reply 0 retweets 0 likes
        3. Sir Panda (Zad Rafi)‏ @dailyzad 26 May 2019
          Replying to @GidMK

          The contribution it has to the summary effect is interesting, but not sure if the analysis excluding it is more robust. Heterogeneity variance is a part of life and estimators need to account for it, would've been better to use REML or HKSJ rather than DL given the # of studies

          1 reply 0 retweets 1 like
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