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If i perform PCA and compress the number of covariates into a set of principal 'distinct' components, how can i statistically determine which of my raw covariates map to which components

Anon
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  • If the general answers in the duplicate don't fully answer your question, take a look at [some of the other threads on PCA](https://stats.stackexchange.com/questions/2691/making-sense-of-principal-component-analysis-eigenvectors-eigenvalues): they contain a wealth of detail. – whuber Jan 28 '22 at 00:17
  • Thank you @whuber however I am specifically asking about how to map original covariate to their associate components? – Anon Jan 28 '22 at 00:25
  • That's standard PCA output. Because it can be confusing, we have several threads discussing the details. A good way to find them is to search our site for "PCA" and focus on [users who have specialized in PCA questions](https://stats.stackexchange.com/tags/pca/topusers), especially [amoeba](https://stats.stackexchange.com/users/28666/amoeba) and [ttnphns](https://stats.stackexchange.com/users/3277/ttnphns). – whuber Jan 28 '22 at 14:12

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