I have a spectrum data (wavelength(x) versus absorption(y)) for 25 unique samples that is almost exactly to the problem presented in this thesis: https://brage.bibsys.no/xmlui//bitstream/handle/11250/2371385/12296_FULLTEXT.pdf?sequence=1&isAllowed=y.
I have about 10 samples that are one kind of biological sample and 15 that are another. For each sample there are 6 highly similar but different replicates (for a total of 25x6 datasets).
My thoughts are to:
- Average the Y values to produce a single dataset,
- Randomly pick one replicate for each sample and throw the others away,
- Treat all replicates as unique individual observations (essentially 125 of them), or
- Something else.
I suspect that; #1 is invalid, #2 will end up losing a lot of data, and #3 is statistically improper.
What is the correct solution?