Linear theory, dimensional theory, and the face-inversion effect.

We contrast 2 theories within whose context problems are conceptualized and data interpreted. By traditional linear theory, a dependent variable is the sum of main-effect and interaction terms. By dimensional theory, independent variables yield values on internal dimensions that in turn determine performance. We frame our arguments within an investigation of the face-inversion effect--the greater processing disadvantage of inverting faces compared with non-faces. We report data from 3 simulations and 3 experiments wherein faces or non-faces are studied upright or inverted in a recognition procedure. The simulations demonstrate that (a) critical conclusions depend on which theory is used to interpret data and (b) dimensional theory is the more flexible and consistent in identifying underlying psychological structures, because dimensional theory subsumes linear theory as a special case. The experiments demonstrate that by dimensional theory, there is no face-inversion effect for unfamiliar faces but a clear face-inversion effect for celebrity faces.