varied four monocular cues to perceived depth in a factorial design. Subjects judged the distance between test objects. Given main effects in the analysis of variance, the authors concluded that the perceivers integrated the four different sources of information, as opposed to simply selecting a single source. Given no interactions in the analysis of variance, the authors concluded that the integration process was additive rather than multiplicative. The ambiguity inherent in Bruno and Cutting's experiments and analyses is discussed. As presented, their results did not provide evidence for integration of depth cues or evidence for additivity, independence, and parallel processing of the cues. An additional analysis of the distribution of the rating judgments given by their subjects, however, provides some evidence for integration of the cues. The fuzzy logical model of perception (FLMP) is extended to describe perceptual recognition of depth. The model assumes independence of the cues during feature evaluation and a nonadditive integration process in which the least ambiguous cues have the greatest impact on the judgment. The FLMP is contrasted with a model assuming additivity of the cues. Because both models describe the results equally well, it remains for future researchers to provide definitive tests between the models. A person's impressive resolution of the visual world might be a consequence of having multiple sources of information about it. Among other things, these sources of information or cues specify the (exocentric) distance between two objects. Although these cues probably overspecify distance, it is not surprising that typical experiments underspecify what the cues are and how they are processed. Bruno and Cutting's (1988) experimental analysis of exocentric distance was a step forward because it improved on the classic single-factor design. The prototypical experiment in visual perception has been to eliminate or to hold constant all potential cues but one, vary the cue of interest, and observe its behavioral consequences. The single-factor design is weak in information value, however, because it cannot measure the relative salience of the cues or address the processing of multiple cues. Given that all cues but one are neutralized, the single-factor design might also overestimate the contribution of the cue being manipulated. Bruno and Cutting's use of a factorial design has the potential to address several important issues that cannot be addressed by the single-factor design (Anderson, 1981; Massaro, 1985 Massaro, , 1987 .
Probably the best known of such models is the fuzzy logical model of perception (FLMP) of REF Massaro & Friedman, 1990 ).
Ambiguity in perception and experimentation
J Exp Psychol Gen
Psychology Medicine