First of all, a very interesting topic.
Before jumping guns, the most important question: WHAT IS YOUR OBJECTIVE? What is the aim of your project?
Just had a quick look at your data.
I am never comfortable working out means for variables which has scale measurements. The reason being the uncertainity in uniformity of scale. For example, is the difference in pain between 2 and 3 same as the difference in pain between 7 and 8? (I don't know). If the scale doesn't represent the severity adequately, I would be more inclined towards simple frequency table. You can take the difference in pain score, and do the frequency table. A lot of negatives will suggest reduced pain.
# For your pain measurements (post-pre) # Frequency counts (VAS) Diff -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 Freq 6 2 11 9 6 8 9 13 10 7 16 1 2 2 1 As can be seen a lot of negatives suggesting the pain relief post treatment.
I understand it is a research work and you'll like to explore new things based on the data you have in hand. However, the objectives has to be set out before collecting the data (forget before analyzing). Changing objectives after seeing the data is not a very good idea.If anyone has any suggestions on where we can go next with this data, it would be truley wonderful.
The generic things to try are look at the side effects
Again its all great running a bunch of exploratory analysis but you have hold back and answer. Do they add something to answering the objectives of your research?We have for sure tried, everything from correlations, multiple regressions, t-tests until the cows come home and various data mining techniques. We have been using Dytham C. 3rd edition to try and filter out any relevant information.