Maybe? I'd have to look at it to know whether I could. Is this something that's on google books? NM I'll look myself.
On Wed, Feb 15, 2012 at 7:11 PM, Larry C. Lyons <[email protected]>wrote: > > Forgot to mention the really difficult part is correctly figuring out the > range of those results. A good well controlled study will have a very > narrow range. A study that has problems with reliability, sample size, etc, > will have a very wide range. Another way to look at it is if the range of > differences encompasses 0 by any substantial amount, most likely it means > that the differences are not meaningful. > > Speaking of such, I'm prepping a statistical criticism of the latest book > byCharles Murray, author of the Bell Curve. Want to join in? > > > On Wednesday, February 15, 2012, Larry C. Lyons <[email protected]> > wrote: > > You are not the only one. On my desk at home is a notebook with all my > notes for the next version of my meta-analysis application. 150 pages and > counting - most of which are botched formulae for calculating statistical > power effect sizes and converting obtained probability values to effect > sizes. Makes me wish at times I stayed with single case designs. > > > > 10 word or less that is really difficult. Can I go for 30? > > > > But you've essentially got the idea. I left out a lot, range estimation > and correction for error andthat sort of thing, but yes. > > > > On Wednesday, February 15, 2012, Dana <[email protected]> wrote: > >> > >> what not really -- the meaning of standard deviations? If so yeah you > are > >> right, I think but what Maureen and I said is an .... ok 10 words or > less > >> version. > >> > >> In this case p=0.011 so theoretically if they did everything else right, > >> these results should replicate 99% of the time. And not, 1%. > >> > >> I realize that's it's not a given that the 1% is random or that it won't > >> occur the next time you repeat the experiment, but I think that is a > rather > >> fine distinction for our purposes. Kinda like the difference between > >> Springfield and Tyson's Corner, as seen from California, yanno? If I > don't > >> have that right then fine, tell me, but if you're going to crank up > your > >> statistical powers I'd rather hear an explanation of that leave one out > >> thing they did a thousand times, because that part I do not understand > at > >> ALL. > >> > >> On Wed, Feb 15, 2012 at 6:21 PM, Larry C. Lyons <[email protected] > >wrote: > >> > >>> > >>> Not really. It depends on the stats that are used. When looking at > >>> statistical results, the way to interpret statistical significance is > as > >>> follows. Let's say the researchers found the two groups showed a > >>> significant difference of p < 0.05 . This means that if you > replicated > >>> the study an infinite number of times, 95% of these results would fall > very > >>> close to the difference found in the first study. How meaningful that > >>> spread is depends on the standard error of the studies, and other > factors. > >>> It also mean that in order to show a significant difference with a > smaller > >>> sample you'd need a much larger difference to achieve statistical > >>> significance. > >>> > >>> So you can make very accurate predictions based on fairly small > samples. It > >>> all depends on the statistical power of your experiment. I'm too burned > out > >>> to really discuss it now, but if interested Wikipedia has a pretty good > >>> explanation of it - http://en.wikipedia.org/wiki/Statistical_power > >>> > >>> On Wednesday, February 15, 2012, LRS Scout <[email protected]> wrote: > >>> > > >>> > The sampling of 90 people is really really small. > >>> > > >>> > On Wed, Feb 15, 2012 at 7:29 PM, Dana <[email protected]> > wrote: > >>> > > >>> >> > >>> >> feel free to run away, Sam, but you still haven't showed me any > basis at > >>> >> all for the crap you've been talking. > >>> >> > >>> >> On Wed, Feb 15, 2012 at 4:18 PM, Sam <[email protected]> wrote: > >>> >> > >>> >> > > >>> >> > I give up and feel the fool for not heeding this advice sooner: > >>> >> > > >>> >> > Dont argue with idiots. They drag you down to their level and > beat > >>> >> > you with experience > >>> >> > > >>> >> > . > >>> >> > > >>> >> > On Wed, Feb 15, 2012 at 7:07 PM, Dana <[email protected]> > wrote: > >>> >> > > > >>> >> > >> > >>> >> > >> Yes it is. It's the same study done three times. Two people, 90 > >>> people > >>> >> > >> and 28 people. > >>> >> > >> > >>> >> > > > >>> >> > > Ah, here's the heart of the problem. No, Sam, it isn't. It's -- > I'd > >>> >> call > >>> >> > it > >>> >> > > two studies and an experiment I guess -- that tested the same > >>> >> hypothesis. > >>> >> > > According to your nomenclature here, all trials for the same > drug > >>> are a > >>> >> > > single study. And mutually responsible for one another's > >>> methodology. > >>> >> > And, > >>> >> > > according to you, everything anyone remotely affiliated with > them > >>> may > >>> >> > have > >>> >>> >> > > > with > > ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~| Order the Adobe Coldfusion Anthology now! http://www.amazon.com/Adobe-Coldfusion-Anthology/dp/1430272155/?tag=houseoffusion Archive: http://www.houseoffusion.com/groups/cf-community/message.cfm/messageid:346967 Subscription: http://www.houseoffusion.com/groups/cf-community/subscribe.cfm Unsubscribe: http://www.houseoffusion.com/groups/cf-community/unsubscribe.cfm
