If you want to discover groupings in your data-set I would have thought
latent class analysis was a more principled solution. There are several
packages for doing this.
If you want more detail about this you might be better asking on
stats.stackexchange.com for statistical help. When you do be sure to
define what you mean by 'do not have a measure' as it is not, to me at
least, clear what s/he means.
On 26/01/2017 13:20, Dr.Vinay Pitchika wrote:
Hello everyone,
I have been analyzing dietary pattern data obtained via FFQ. We performed
Principal Component Analysis and decided to extract 3 dimensions (healthy,
unhealthy and mixed diet) and to adjust this in linear regression model
along with various other variables. However, our statistician was not happy
with the approach because the 3 dimensions we adjust do not have a measure.
So, I would like to classify the patients in our dataset using the PCA
results. Is it possible to classify all the patients into one of the 3
groups mentioned above?
Thank you
Vinay
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Michael
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