Unfolding persons' personal values in ideal-point and vector models

Similarities and differences of individuals' ratings of the importance of personal values have recently been explained by the ideal-point unfolding (IPU) model. The IPU assumes that there is a geometric configuration of value points, shared by all individuals, and an ideal point that is special for each person. The distances between the ideal points and the value points correspond to the observed importance ratings. The IPU is psychologically conclusive but difficult to fit. We here investigate whether an alternative individual differences model, the vector model of unfolding (VMU), is a viable alternative to the IPU. The VMU represents individuals as vectors whose lengths and directions in value space explain the observed preferences. The VMU has an analytic solution, robust scaling algorithms, and unique solutions if properly normalized. The psychological assumptions of the VMU are simpler than those of the IPU. This makes the VMU attractive as a model for fast and frugal judgments such as responding to an anonymous questionnaire and for quickly diagnosing inter-individual differences.