Dear subscribers,
Thank you very much for your comments regarding my data analysis question.
Best wsihes,
Nikolaos Pandis
--- On Tue, 7/29/08, Sven-Oliver Spie� <[email protected]> wrote:
> From: Sven-Oliver Spie� <[email protected]>
> Subject: RE: st: Help on data analysis strategy
> To: [email protected]
> Date: Tuesday, July 29, 2008, 10:06 PM
> Before performing inferential analyses I find it often
> helpful to plot the
> data, e.g. means of the two groups over time for each of
> the four outcomes.
>
> Also since outcomes are measured on a 6 point scale you
> could consider
> treating them as interval data. That would most likely be
> easier for
> computation and interpretation. If in doubt do both and see
> if you would
> come to different conclusions. If the conclusions are equal
> you can use the
> simpler model(s) and just add a footnote that substantially
> the results are
> the same even if "proper" model(s) are used.--Of
> course that depends on your
> audience.
>
> Best,
> Sven-Oliver
>
>
>
> > -----Original Message-----
> > From: [email protected]
> [mailto:owner-
> > [email protected]] On Behalf Of
> Lachenbruch, Peter
> > Sent: Tuesday, July 29, 2008 7:51 PM
> > To: [email protected]
> > Subject: RE: st: Help on data analysis strategy
> >
> > While this may be solid advice to experienced
> statisticians and Stata
> > users, I would be a bit concerned about letting a
> novice loose on
> > GLLAMM
> > - it's tough sledding for most experienced users.
> >
> > Tony
> >
> > Peter A. Lachenbruch
> > Department of Public Health
> > Oregon State University
> > Corvallis, OR 97330
> > Phone: 541-737-3832
> > FAX: 541-737-4001
> >
> >
> > -----Original Message-----
> > From: [email protected]
> > [mailto:[email protected]] On
> Behalf Of David Airey
> > Sent: Tuesday, July 29, 2008 8:09 AM
> > To: [email protected]
> > Subject: re: st: Help on data analysis strategy
> >
> > .
> >
> > My text was stripped in my reply.
> >
> > There is a chapter (#7) in Multilevel and Longitudinal
> Modeling Using
> > Stata (Stata Bookstore) that describes mixed models
> for ordinal data
> > using the command GLLAMM from ssc. This is what you
> need.
> >
> > -Dave
> >
> >
> >
> >
> > > Dear subscribers,
> > >
> > > I am new to statistics and Stata, and I would
> like to ask for
> > > advice, if I amy, regarding the type analysis for
> a clinical
> > > experiment.
> > >
> > > We have 2 groups of patients, 30 in each group
> that undergo surgery
> > > and receive either standard medication or a new
> medication to help
> > > recovery.
> > >
> > > Both groups are asked 4 questions regarding for
> example pain,
> > > inflammation ect and they are required to give an
> answer that gets a
> > > score from 0 to 5.
> > > All 4 questions are asked repeatedly for day0
> (before treatment)
> > > day1, day2, day3, day5 and day7.
> > >
> > > The objective of the study is to see if there is
> a difference
> > > between the control and the experimental group as
> determined by the
> > > answers to the four questions.
> > >
> > > Some of the ideas I have are the following:
> > >
> > > 1. Perform a Mann Whitney test, ordinal data,
> between the control
> > > and the experimental group at each day and for
> each question
> > > separately.
> > >
> > > 2. Define an endpoint per question. For example
> for the question on
> > > pain define as endpoint when the answer is no
> pain, and use right
> > > sencoring for persistent pain after day7. Perform
> a survival
> > > analysis for each question and compare the
> survival curves for the 2
> > > groups.
> > >
> > > 3. Convert to binary data, for example pain=yes
> for score 1 to 5,
> > > and pain= no for score 0. Perform logistic
> regression and evaluate
> > > the effect of treatment separately for every
> question.
> > >
> > > Your advice would be greatly appreciated.
> > >
> > > I understand the above questions might be of
> limited interest to
> > > most subscribers but, anyways, I would like to
> thank you for your
> > > consideration.
> > >
> > > Best regards,
> > >
> > > Nikolaos Pandis
> >
> > *
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