# re: st: Help on data analysis strategy

 From David Airey To statalist@hsphsun2.harvard.edu Subject re: st: Help on data analysis strategy Date Tue, 29 Jul 2008 10:09:26 -0500

.

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.

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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