1. Re: Polychoric Principal Component Analysis

Originally Posted by spunky
what about calculating a factor/principal component score on the PC that represents "wealth"? i'm assuming "wealth" is a latent variable here where you're using items as proxies, so certain proxies would be more correlated with this PC that stands for "wealth"? if you get a PC score, you would get a measure of this "wealth" per individual.
Yes, I just wanted to retain the first principal component as an indicator of wealth, so I could work with this PC as a measure of "wealth" per individual as you said.
But when I used the principal function I got PC1 for each of my "items" (variables).

http://imgur.com/gcqREq8

How do I get a PC for every individual?

2. Re: Polychoric Principal Component Analysis

Yes, I want to get a PC of "wealth" per individual, but when I use the principal function I get a PC score for every variable and not for every individual/observation. Is there a way to do that?

http://s17.postimg.org/51ygmy233/Scr...7_47_22_PM.png

3. Re: Polychoric Principal Component Analysis

what about the option that i mentioned to you regarding calculating principal component scores from the principal component that implies the latent variable 'wealth'?

that way you would obtain a reading of 'wealth' for each participant.

other than that, i cannot see any other possibility to get information of 'wealth' per individual. if the scores don't work for you i don't think principal component is then the technique you should be using to get the information you want.

4. Re: Polychoric Principal Component Analysis

Yes I want to do that, but I don't know how to do it. I know this isn't a space for R questions, but the only result I get is the one (the picture) I uploaded in the post above.

This are the only functions I am using:

ses <- read.table("SES_matrix_edit.txt", fill = T)
Poly_cor <- polychoric(ses)\$rho
principal(Poly_cor, nfactors = 1)

Thank you again.

5. Re: Polychoric Principal Component Analysis

Originally Posted by JavierM88
but I don't know how to do it.
i think all the info you need about principal component scores can be found here

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