I need to run a stats analysis on data at the bottom of this post. Essentially, I want to investigate whether Diet Group (categorical independent var) or # of Stitches (categorical independent var) affects Score (ordinal dependent var).
From what I understand, I would need to use a non-parametric test as my data doesn't seem to be normal / there isn't enough to convince me that I have a normal dataset. This would mean that I can't use a two-way ANOVA (which I was originally recommended) to investigate all three variables together.
From my discussions, I believe I should be conducting two Mann-Whitney U tests (one for Diet Group vs. Score and one for # of Stitches vs. Score. However, as my dependent var (Score) essentially falls mostly within two groups (either 1 or 2) even though the scoring scale itself is 0 - 4, I was informed that these ranked tests wouldn't be ideal as they don't do well when there are lots of ties within the ranking.
Are there any other statistical tests that I should be using with this non-ideal data set or is Mann-Whitney U the best I'd be able to do?
Raw Data:
animal | diet group | # stitches | score |
---|---|---|---|
A | ED | 5 | 2 |
B | ED | 5 | 0 |
C | ED | 5 | 2 |
D | ED | 5 | 1 |
E | ED | 5 | 1 |
F | ED | 5 | 1 |
G | ED | 5 | 1 |
H | ED | 5 | 2 |
I | ED | 5 | 2 |
J | WD | 5 | 2 |
K | WD | 5 | 2 |
L | WD | 5 | 2 |
M | WD | 5 | 2 |
N | WD | 5 | 1 |
O | ED | 7 | 2 |
P | WD | 7 | 1 |
Q | WD | 7 | 2 |
R | WD | 7 | 2 |
S | WD | 7 | 2 |
T | WD | 7 | 2 |