-- David B. Wilson, Ph.D. Associate Professor Chair, Administration of Justice Department George Mason University 10900 University Boulevard, MS 4F4 Manassas, VA 20110-2203 Phone/Fax: 703.993.4701 dwilsonb_at_gmu.edu http://mason.gmu.edu/~dwilsonb/home.html > Stevan Harnad wrote: >> Phil, >> Thanks for the helpful feedback. >> >> I'm afraid you're mistaken about meta-analysis. It can be a >> perfectly appropriate statistical technique for analyzing a large >> number of studies, with positive and negative outcomes, varying >> in methodological rigor, sample size and effect size. It is a way >> of estimating whether or not there is a significant underlying >> effect. >> >> I think you may be inadvertently mixing up the criteria for (1) >> eligibility and comparability for a meta-analysis with the >> criteria for (2) a clinical drug trial (for which there rightly >> tends to be an insistence on randomized control trials in >> biomedical research). >> >> Now I would again like to take the opportunity of receiving this >> helpful feedback from you to remind you about some feedback I >> have given you repeatedly http://bit.ly/dkieVi on your own 2008 >> study -- the randomized control trial that you suggest has been >> the only methodologically sound test of the OA Advantage so far: >> >> You forgot to do a self-selection control condition. That would >> be rather like doing a randomized control trial on a drug -- to >> show that the nonrandom control trials that have reported a >> positive benefit for that drug were really just self-selection >> artifacts -- but neglecting to include a replication of the >> self-selection artifact in your own sample, as a control. >> >> For, you see, if your own sample was too small and/or too brief >> (e.g., you didn't administer the drug for as long an interval, or >> to as many patients, as the nonrandom studies reporting the >> positive effects had done), then your own null effect with a >> randomized trial would be just that: a null effect, not a >> demonstration that randomizing eliminates the nonrandomized drug >> effect. (This is the kind of methodological weakness, for >> example, that multiple studies can be weighted for, in a >> meta-analysis of positive, negative and null effects.) >> >> [I am responding to your public feedback here, on the liblicense >> and SERIALST lists, but not also on your SSP Blog, where you >> likewise publicly posted this same feedback (along with other, >> rather shriller remarks) http://j.mp/d91Jk2 because I am assuming >> that you will again decline to post my response on your blog, as >> you did the previous time that you publicly posted your feedback >> on my work both there http://bit.ly/8LK57u and elsewhere -- >> refusing my response on your blog on the grounds that it had >> already been publicly posted elsewhere!...] >> >> -- Stevan Harnad >> >> PS The idea of doing a meta-analysis came from me, not from Dr. >> Swan. >Received on Wed Mar 17 2010 - 19:14:22 GMT
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