Hey Folks:
I am trying to define groups within a dataset of water-quality analyses.
The data need to be analyzed with non-parametric statistics. However, I
am unsure of my current approach (See below).
Current Procedure:
Step 1: Non-metric Multidimensional Scaling (Euclidean Distance on Scaled
Data)
Step 2: Hierarchical Cluster Analysis (Wards Method, Euclidean Distance
of NMDS coordinates)
Step 3: Multi-response Permutation Procedure (Euclidean distance of the
rank-transformed waterquality data, groups defined by Step 2)
Question:
Since NMDS coordinates are non-normal, I am violating the assumptions
behind the Ward's clustering algorithm. However, according to the MRPP
test, the groups are significantly different. Since MRPP is a
non-parametric test, can I justify using the groups defined through
clustering?
Any suggestions and/or advice would be greatly appreciated.
Thanks!
Nate Jones
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