I am using XLStat for a PCA of time-series water chemistry data. I have 23 analytes and 29 samples. I am using a correlation matrix for PCA as I find it more interpretable in the context of hydrochemistry. The data is also standardized to a variance of 1 and a mean of 0 to avoid the effect of differing units.
The results of the PCA look great. Very easy to interpret and everything makes a lot of sense. There are numerous significant correlations present in the correlation matrix(alpha=0.5). A KMO sampling adequacy test yields a value of 0.64. The problem is that I keep having an observed chi-squared of "-Inf" for Bartlett's Sphericity Test. Essentially, this means that the chi-squared could not be computed.
What is going on here? This value makes no sense given the strong correlations in the matrix.
Can I continue with PCA despite the failed test?
Could the problem be that by normalizing the data I am imposing normality upon it falsely?