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From |
Sven-Oliver Spieß <mail@svenoliverspiess.net> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Help on data analysis strategy |

Date |
Tue, 29 Jul 2008 21:06:12 +0200 |

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: owner-statalist@hsphsun2.harvard.edu [mailto:owner- > statalist@hsphsun2.harvard.edu] On Behalf Of Lachenbruch, Peter > Sent: Tuesday, July 29, 2008 7:51 PM > To: statalist@hsphsun2.harvard.edu > 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: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of David Airey > Sent: Tuesday, July 29, 2008 8:09 AM > To: statalist@hsphsun2.harvard.edu > 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 > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: Help on data analysis strategy***From:*Nikolaos Pandis <npandis@yahoo.com>

**References**:**re: st: Help on data analysis strategy***From:*David Airey <david.airey@vanderbilt.edu>

**RE: st: Help on data analysis strategy***From:*"Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>

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