Hey, Joshua
Thank so much for your quick response.  Those examples you produced are
very good, I'm pretty impressed by the graphs.  When I ran the last line, I
hit an error, so I ran what's inside summary(), it give me

Error: could not find function "lmer"

Something with the package "lme4"?
Colin


On Sun, Nov 20, 2011 at 1:00 AM, Joshua Wiley <jwiley.psych@gmail.com>wrote:

> Hi Colin,
>
> I have never heard of a binomial distribution z statistic with (or
> without for that matter) a continuity correction, but I am not a
> statistician.  Other's may have some ideas there.  As for other ways
> to analyze the data, I skimmed through the article and brought the
> data and played around with some different analyses and graphs.  I
> attached a file headache.txt with all the R script (including the data
> in an Rish format).  It is really a script file (i.e., .R) but for the
> listservs sake I saved it as a txt.  There are quite a few different
> things I tried in there so hopefully it gives you some ideas.
> Regardless of the analysis type used and whether one considers
> proportion that "significantly improved" or the raw frequency or
> intensity scores, I would say that concluding the treatment was
> effective is a good conclusion.  The only real concern could be that
> people would naturally get better on their own (a control group would
> be needed to bolster the causal inference drawn from a pre/post
> measurement).  However, given at least what I know about migraines, it
> is often a fairly chronic condition so over a relatively short time
> period, it seems implausible to conclude that as many people would be
> improving as this study reported.
>
> Cheers,
>
> Josh
>
> On Sat, Nov 19, 2011 at 7:43 PM, Colstat <colstat@gmail.com> wrote:
> > hey, Joshua
> > I was reading this paper, in attachment, and reproducing the results.
> >
> > I was really confused when he said in the paper "The results were then
> > statistically analyzed using binomial distribution z statistics with
> > continuity correction."  The data is binomial?  To me, this is a paired
> > t-test.
> >
> > What command should I use to get those results (the first paragraph in
> > Results section)?  Basically, it's a pre and post treatment problem.
> >
> > What other graphical analysis do you think is appropriate? reshape
> package?
> > lattice package, namely conditional graph?
> >
> > I know this might be too much, but I do really appreciate it if you do
> take
> > a look at it.
> >
> > Thanks,
> > Colin
> >
> >
> > On Sat, Nov 19, 2011 at 10:15 PM, Joshua Wiley <jwiley.psych@gmail.com>
> > wrote:
> >>
> >> Hi,
> >>
> >> I am not clear what your goal is.  There is a variety of data there.
> >> You could look at t-test differences in preIntensity broken down by
> >> sex, you could use regression looking at postIntensity controlling for
> >> preIntensity and explained by age, you could....
> >>
> >> Why are you analyzing data from an article?  What did the article do?
> >> What you mention---some sort of z statistic (what exactly this was of
> >> and how it should be calculated did not seem like was clear even to
> >> you), histogram, t-test, lattice, are all very different things that
> >> help answer different questions, show different things, and in one is
> >> a piece of software.
> >>
> >> Without a clearer question and goal, my best advice is here are a
> >> number of different functions some of which may be useful to you:
> >>
> >> ls(pos = "package:stats")
> >>
> >> Cheers,
> >>
> >> Josh
> >>
> >> On Sat, Nov 19, 2011 at 3:01 PM, Colstat <colstat@gmail.com> wrote:
> >> > 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.
> >> >
> >>
> >>
> >>
> >> --
> >> Joshua Wiley
> >> Ph.D. Student, Health Psychology
> >> Programmer Analyst II, ATS Statistical Consulting Group
> >> University of California, Los Angeles
> >> https://joshuawiley.com/
> >
> >
>
>
>
> --
> Joshua Wiley
> Ph.D. Student, Health Psychology
> Programmer Analyst II, ATS Statistical Consulting Group
> University of California, Los Angeles
> https://joshuawiley.com/
>

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