You need a statistician or at least someone who's take a stats course in the last 10 years but it may be what the author was trying to get at.
At least the binomial is descrete as is the z so it may be that the z was used as easier to calculate than a binomial? How old is the paper. Before, let's say the early 1980s a lot of people were still doing stats by hand (IIRC, even calculators were relatively expensive and rare and calculating a binomial of any size was close to impractical.-- I tried it once). So using a z-distribution with Yates correction made sense. It's a little like early factor analysis when rotate the factors actually meant rotate the glass plates. --- On Sun, 11/20/11, Colstat <cols...@gmail.com> wrote: From: Colstat <cols...@gmail.com> Subject: Re: [R] Data analysis: normal approximation for binomial To: "John Kane" <jrkrid...@yahoo.ca> Cc: r-help@r-project.org Received: Sunday, November 20, 2011, 10:10 PM Hey, John I like the explicit formula they put in there. I looked around last night and found this http://www.stat.yale.edu/Courses/1997-98/101/binom.htm which is basically normal approximation to the binomial, I thought that was what the author was trying to get at? Colin On Sun, Nov 20, 2011 at 8:49 AM, John Kane <jrkrid...@yahoo.ca> wrote: Hi Colin, I'm no statistician and it's been a very long time but IIRC a t-test is a 'modified version of a x-test that is used on small sample sizes. (I can hear some of our statistians screaming in the background as I type.) In any case I thing a Z distribution is descrete and a standard normal is not so a user can use Yates continuity correction to interpolate values for the normal between the discrete z-values. Or something like this. I have only encountered it once in a Psych stats course taught by an animal geneticist who seemed to think it was important. To be honest, it looked pretty trivial for the type of data I'd be likely to see. I cannot remember ever seeing a continuity correction used in a published paper--for that matter I have trouble remembering a z-test. If you want more information on the subject I found a very tiny bit of info at http://books.google.ca/books?id=SiJ2UB3dv9UC&pg=PA139&lpg=PA139&dq=z-test+with+continuity+correction&source=bl&ots=0vMTCUZWXx&sig=bfCPx0vynGjA0tHLRAf6B42x0mM&hl=en&ei=nQHJTo7LPIrf0gHxs6Aq&sa=X&oi=book_result&ct=result&resnum=2&ved=0CC0Q6AEwAQ#v=onepage&q=z-test%20with%20continuity%20correction&f=false A print source that, IIRC, has a discussion of this is "Hayes, W. (1981. Statistics. 3rd Ed., Holt Rinehart and Winston Have fun --- On Sat, 11/19/11, Colstat <cols...@gmail.com> wrote: > From: Colstat <cols...@gmail.com> > Subject: [R] Data analysis: normal approximation for binomial > To: r-help@r-project.org > Received: Saturday, November 19, 2011, 6:01 PM > Dear R experts, > > I am trying to analyze data from an article, the data looks > like this > > Patient Age Sex Aura preCSM preFreq preIntensity postFreq > postIntensity > postOutcome > 1 47 F A 4 6 9 2 8 SD > 2 40 F A/N 5 8 9 0 0 E > 3 49 M N 5 8 9 2 6 SD > 4 40 F A 5 3 10 0 0 E > 5 42 F N 5 4 9 0 0 E > 6 35 F N 5 8 9 12 7 NR > 7 38 F A 5 NA 10 2 9 SD > 8 44 M A 4 4 10 0 0 E > 9 47 M A 4 5 8 2 7 SD > 10 53 F A 5 3 10 0 0 E > 11 41 F N 5 6 7 0 0 E > 12 49 F A 4 6 8 0 0 E > 13 48 F A 5 4 8 0 0 E > 14 63 M N 4 6 9 15 9 NR > 15 58 M N 5 9 7 2 8 SD > 16 53 F A 4 3 9 0 0 E > 17 47 F N 5 4 8 1 4 SD > 18 34 F A NA 5 9 0 0 E > 19 53 F N 5 4 9 5 7 NR > 20 45 F N 5 5 8 5 4 SD > 21 30 F A 5 3 8 0 0 E > 22 29 F A 4 5 9 0 0 E > 23 49 F N 5 9 10 0 0 E > 24 24 F A 5 5 9 0 0 E > 25 63 F N 4 19 7 10 7 NR > 26 62 F A 5 8 9 11 9 NR > 27 44 F A 5 3 10 0 0 E > 28 38 F N 4 8 10 1 3 SD > 29 38 F N 5 3 10 0 0 E > > How do I do a binomial distribution z statistics with > continuity > correction? basically normal approximation. > Could anyone give me some suggestions what I (or R) can do > with these data? > I have tried tried histogram, maybe t-test? or even > lattice? what else can > I(or can R) do? > help please, thanks so much. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org > mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, > reproducible code. > [[alternative HTML version deleted]]
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