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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. Chad Senger‏ @chad_senger Jul 28
      Replying to @GidMK

      This is of course true. But not unique to meta analysis, so it’s not clear why your focusing on them. A poorly run large scale double blind randomized control trial is just as worthless if it’s run poorly. A meta analysis could at least overcome a bad study with the aggregate

      1 reply 0 retweets 0 likes
    2. Health Nerd‏Verified account @GidMK Jul 28
      Replying to @chad_senger

      That is not true actually. Meta-analyses can be biased by bad studies in a number of ways, often to do with the weighting. Sometimes a single bad study can push the entire model in a single direction

      1 reply 0 retweets 0 likes
    3. Health Nerd‏Verified account @GidMK Jul 28
      Replying to @GidMK @chad_senger

      The rest of your statement confuses me. I talk all the time about bad study design, but *this* conversation is about meta-analysis

      1 reply 0 retweets 0 likes
    4. Chad Senger‏ @chad_senger Jul 28
      Replying to @GidMK

      No it’s not, it’s about poorly run studies and bad data. You said it yourself, meta analysis’ are very valuable with good data properly run studies. The flaw you are picking on is not in the meta analysis at all, it’s in bad studies.

      1 reply 0 retweets 0 likes
    5. Health Nerd‏Verified account @GidMK Jul 28
      Replying to @chad_senger

      The point I was making is that meta-analysis does not "correct" for bad data in any way, nor does it resolve underlying issues with the research

      1 reply 0 retweets 0 likes
    6. Chad Senger‏ @chad_senger Jul 28
      Replying to @GidMK

      And no one is saying it does. But it only takes a cursory understanding of meta analysis to know that if you pool studies with different approaches/treatments, in different populations/ cultures... you are going to dampen the effect those outside influences have on your result

      1 reply 0 retweets 0 likes
    7. Health Nerd‏Verified account @GidMK Jul 28
      Replying to @chad_senger

      That is simply incorrect. Entirely wrong

      1 reply 0 retweets 1 like
    8. Chad Senger‏ @chad_senger Jul 28
      Replying to @GidMK

      Let’s say a study got the dosage too low. They didn’t see a significant effect from the treatment but not because it didn’t work, but because they got the dosage wrong. A meta analysis that includes studies with higher dosages will help correct for that.

      1 reply 0 retweets 0 likes
    9. Health Nerd‏Verified account @GidMK Jul 28
      Replying to @chad_senger

      That's not true at all. If the study found no treatment effect because the dosage was wrong, it would bias the model towards a null finding even though there was indeed an effect. Depending on the situation, it could entirely remove the evidence for an effective drug

      1 reply 0 retweets 0 likes
    10. Chad Senger‏ @chad_senger Jul 28
      Replying to @GidMK

      Yes, it will bias the model, but if it were a single study (the alternative to a meta analysis) you’d lose the effect entirely. All the inputs bias the model, that’s the point.

      1 reply 0 retweets 2 likes
      Health Nerd‏Verified account @GidMK Jul 28
      Replying to @chad_senger

      You could easily lose the effect entirely BECAUSE you used a meta-analysis. The point is that meta-analysis does nothing to correct for underlying biases

      11:27 PM - 28 Jul 2021
      2 replies 1 retweet 0 likes
        1. New conversation
        2. Garfunkle‏ @FamularoJoel Jul 29
          Replying to @GidMK @chad_senger

          If 58 witnesses related essentially the same event with varying degrees of consistency and credibility, wouldn’t the smart thing to do be to start with an average of all of the stories? Wouldn’t the truth most likely mirror the details that were repeated the most often?

          2 replies 0 retweets 0 likes
        3. Garfunkle‏ @FamularoJoel Jul 29
          Replying to @FamularoJoel @GidMK @chad_senger

          So for example if 18 said they saw a man 5’8 tall, 20 said 5’10 and 20 claimed he was 6ft tall, you’d conclude he was approx 5’10. Either way, surely it wouldn’t make much sense to conclude ‘We have no idea how tall the man was and can’t even conclude if said event took place.’

          0 replies 0 retweets 0 likes
        4. End of conversation
        1. Chad Senger‏ @chad_senger Jul 29
          Replying to @GidMK

          That’s simply untrue. If it were true, large scale trials wouldn’t be any more valuable than small scale trials. The larger the sample, the more corrective it will be for individual bias. This is as true at the study level as it is at the participant level.

          0 replies 0 retweets 1 like
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