Often, perhaps usually, a treatment will make some people better, do nothing for others, and make some people worse.
When a treatment makes about as many people worse as it makes better, then meta-analysts say it doesn’t work.
But often it *does* work - for *some* people. Indeed, it might work very well indeed for them.
The other people - those for whom it makes no difference or makes worse - just need to stop using it - then everyone benefits.
It is just a matter of using patient response as a feedback loop.
Is that really so difficult to understand? - yet I can never get this point across to bio-statisticians/ epidemiologists, meta-analysts and the like…
"Is that really so difficult to understand? - yet I can never get this point across to bio-statisticians/ epidemiologists, meta-analysts and the like…"
ReplyDeleteBut this is not difficult to understand. Indeed, it is just common sense.
Which reminds me; I had a teacher who used to say, "The only trouble with common sense is that it's not the common".
Apropos your post:
ReplyDeletehttp://www.ribbonfarm.com/2010/09/28/learning-from-one-data-point/
In a bureaucratic state, a treatment that will prolong the life and well-being of ten terminal patients is not sufficient if that treatment will kill one terminal patient. And no one will be permitted to choose for himself.
ReplyDeleteA bureaucrat is not paid to understand. Our original mistake was in permitting him any access to decisions.