If your goal is to condense scores on a large number of dependent measures into a smaller set of variables in order to simply data analysis, the best approach to take is
A) principle components analysis.
B) common factors analysis.
C) confirmatory factor analysis.
D) parallel analysis.

Question

Quizplus · Accepted Answer

Principle components analysis is the best approach to condense scores on a large number of dependent measures into a smaller set of variables as it identifies the underlying components that explain the greatest amount of variance in the measures. This method is especially useful when there are high intercorrelations between the measures. Common factors analysis and confirmatory factor analysis are more appropriate when there is prior knowledge or theory about the underlying factors. Parallel analysis is a technique used to determine the number of factors to extract, but it is not used for condensing scores on dependent measures.

If Your Goal Is to Condense Scores on a Large