psych (version 1.0-97)

predict.psych: Prediction function for factor analysis or principal components


Finds predicted factor/component scores from a factor analysis or components analysis of data set A predicted to data set B. Predicted factor scores use the weights matrix used to find estimated factor scores, predicted components use the loadings matrix.


predict.psych(object, data,,...)


the result of a factor analysis or principal components analysis of data set A
Data set B, of the same number of variables as data set A.
if specified, the data set B will be standardized in terms of values from the old data
More options to pass to predictions


  • Predicted factor/components scores.

See Also

fa, principal


Run this code
x <- sim.item(12,500)
f2 <- fa(x[1:250,],2,scores=TRUE)  # a two factor solution
p2 <- principal(x[1:250,],2,scores=TRUE)  # a two component solution
round(cor(f2$scores,p2$scores),2)  #correlate the components and factors from the A set
#find the predicted scores (The B set)
pf2 <- predict(f2,x[251:500,])
pp2 <- predict(p2,x[251:500,])
round(cor(pf2,pp2),2)   #find the correlations in the B set
#test how well these predicted scores match the factor scores from the second set
fp2 <- fa(x[251:500,],2,scores=TRUE)
#note that the signs of the factors in the second set are arbitrary

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