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re: st: Help on data analysis strategy
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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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