These methods test for, or identify, underlying dimensional structures in data at various levels of measurement.  R methods estimate dimensional structure in variables measuring attributes, behaviors, and attitudes.

This technique is especially useful for reducing data collection costs while maintaining measurement validity when multiple items are measuring the same thing are fail to discriminate.  It is also a theoretical alternative to ridge regression for reducing bias from multicollinearity in estimating regression models.