R help - Jan 2012 - PCA for assets based household income analysis (" hetcor" and "princomp")

I am doing Principal Component Analysis (PCA) on assets data for household
income prediction. The problem is that the assets data are rank ordered (usually
binary ... possess car/don't possess car), so the normal correlation is
inappropriate for the calculation of the PCA. Instead one has to use the
polychoric correlation coefficient. It uses the "random.polychor.pa"
package.



Scenario 1
If i only use PCA without using polychoric correlation
assets.pca <- princomp(covmat = assets, scores=T)
assets$income<-predict(assets2.pca)[,1]

# these predict the coefficient for  income for each
observation
Scenario 2
but when i run "hetcor" (for polychoric correlation
coefficient) , and then princomp (for PCA) and finally predict
( to  predict the coefficient for income for
each observation).
hetcor and princomp runs fine but predict
command doesn't work and
it doesn't predict value for each observation
 library(epicalc)library(foreign)library(polycor)
assets.mat <- hetcor(assets, use="complete.obs")[[1]]
 assets.pca <- princomp(covmat = assets.mat,
scores=T)assets$income<-predict(assets.pca)[,1]
the problems are why this "pridict" commend throwing error in
scenario 2 and not in scenario 1?Is there any other way to predict the values
for each observation?
thanks a lotmm

       

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