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  1. #11
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    The WHOs guidelines on meta-analysis is generally the best way to take many small results and to build something more conclusive. The biggest problem is that most 'high profile' studies are controversial for using loaded dice or are in very small sample sizes.

  2. #12
    Dreaming the life onemoretime's Avatar
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    I knew social science wasn't in my future when no one could give me a good reason why the statistical calculations meant a damn thing, and were anything more than some numbers a person pulled out of his ass.

  3. #13
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    Quote Originally Posted by InvisibleJim View Post
    The WHOs guidelines on meta-analysis is generally the best way to take many small results and to build something more conclusive. The biggest problem is that most 'high profile' studies are controversial for using loaded dice or are in very small sample sizes.
    The problem is that even 'high profile' studies with large sample sizes can have flawed methodology, the results of which can be publicised as something it is not. It is possible for example to deviate substantially from a published protocol (relying instead on post-hoc thresholds) and still get published in a top journal such as NEJM or The Lancet.
    But the flaws are not just limited to clinical trials.
    One of the problems is that biomedical systems are complex and the methodology doesn't always help serve to eliminate other hypotheses.

  4. #14
    Senior Member INTP's Avatar
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    this is ridiculous, i could expect this from someone who knows nothing about research, but from a doctor..

    he is talking about bias being one big factor with this. eliminating bias by making the research setting is something that is #1 requirement for research setting..

    naturally some drug company could want to create biased research settings, but the effects this sort of thing going public would be so huge to the company that it might even lose its licenses and it would definitely be prosecuted. researches getting to this sort of thing would never get a job again. all papers on the research are looked through by different authorities on medical field etc etc. so trying to do tricks like this isnt really a good idea, that is unless the government would want biased research on that particular topic also. like what happened with marijuana research back in the days, when they proved marijuana to be lethal and cause brain damage by suffocating some monkeys with marijuana smoke, open their brains and looking at their brains and seeing brain damage..

    and in case you guys didnt know, other researchers can report biased studies to authorities and they will investigate it throughout. if the bias is intentional they will be prosecuted and if the researchers are such newbies that they didnt take care of the bias, they wont be able to get job very easy in the future, because they have kinda ruined their reputation on the field of research.
    "Where wisdom reigns, there is no conflict between thinking and feeling."
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  5. #15
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    As I keep saying much of the bias is not deliberate, at least on the individual level. You have to understand that in the real world, scientific research and especially medical research is both very messy and politicised. I could give you plenty of examples where governments ask for biased research to be done (or worse, research that is impossible), and this is not at all limited to drug trials.
    Secondly, where there is a dominant scientific paradigm, it is often very easy to do the 'tricks' (eg not sticking to the protocol) that I mentioned above because it produces the result that everyone involved 'wanted' to see.

  6. #16
    That chalkboard guy Matthew_Z's Avatar
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    Type I errors are a bitch.

    Remember kids, keep your α-levels under control.
    If a deaf INFP falls in the forest and no one is around to hear it, does it make a sound?

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    Sometimes it's not merely about alpha levels, but rather whether you are measuring the relevant confounding variables which may bias the result. When reading most papers, it is usually very easy to find potential biases that have not been fully accounted for.

    Here is Dr Ioannidis' latest article:
    "Comparison of Effect Sizes Associated With Biomarkers Reported in Highly Cited Individual Articles and in Subsequent Meta-analyses"
    http://jama.ama-assn.org/content/305/21/2200.short

    No significant biomarkers have been for cancer have made it to the clinic for the past 25 years, despite around $100 billion dollars spent on cancer research.

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