Thinking Ahead: Assuming Linear Versus Nonlinear Personality-Criterion Relationships in Personnel Selection
Converse, Patrick D.; Oswald, Frederick L.
Recent studies suggest that the form of some personality-performance relationships may be curvilinear, meaning that traditional top-down selection is inefficient in capitalizing on underlying personality-performance relationships. This study examines how mean performance is affected by how well the selection method is aligned with the nature of personality-criterion relationships. A simulation manipulated the linearity or nonlinear inflection point of predictor-criterion relationships, and several selection approaches were implemented that varied in level of congruence with these relationships. Results indicate that incongruence can produce notable decrements in mean performance under some conditions. Some evidence also suggests that decrements can be greater when linearity is assumed but relationships are nonlinear (vs. when nonlinearity is assumed but relationships are linear), selection ratios are smaller, and a single predictor is used.