predict.psych {psych} | R Documentation |
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.
## S3 method for class 'psych' predict(object, data,old.data,...)
object |
the result of a factor analysis or principal components analysis of data set A |
data |
Data set B, of the same number of variables as data set A. |
old.data |
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.
Thanks to Reinhold Hatzinger for the suggestion and request
William Revelle
set.seed(42) x <- sim.item(12,500) f2 <- fa(x[1:250,],2,scores="regression") # 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) round(cor(fp2$scores,pf2),2) #note that the signs of the factors in the second set are arbitrary