Comparative judgments with missing information: a regression and process tracing analysis.
We had participants decide which one of two applicants was better qualified for a scholarship. They also judged the difference between them (comparative judgment). The applicants were described by features (grades) in different subjects (dimensions). The grades on some dimensions were missing (unique dimensions) for an alternative while all the grades were available on other dimensions (common dimensions). In a conventional regression analysis, we found that decision makers gave more weight to dimensions when they were common than when they were unique. However, this commensurability effect was limited to medium important dimensions and did not apply to dimensions of high or low importance. We also observed how participants retrieved information for the choice alternatives and analysed how importance and commensurability are reflected in the processing prior to the decision. Features on more important or common dimensions were inspected earlier than features on less important or unique dimensions. Participants preferred dimensional transitions and inspected features on unique dimensions longer than their common counterparts. This finding suggested that participants used inferences when features were missing. We propose an outline of a decision heuristic to describe decision making with missing information.