psych (version 1.1.11)

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

Description

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.

Usage

## S3 method for class 'psych':
predict(object, data,old.data,...)

Arguments

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

Value

• Predicted factor/components scores.

See Also

fa, principal

Examples

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