Brunswik's work on probabilistic functionalism in human perception (1934, 1956) is fundamental for multimethod assessment for at least five related reasons. First, recognizing the multidetermination of behavior as a general principle, Brunswik reconcep-tualized perception, impression formation, and clinical judgment from a multivariate perspective. Whereas traditional psychophysics was mainly concerned with the effects of physical stimulus properties, Brunswik expanded the causal scope for the explanation of optical illusions, perceptual constancy, and physiognomic trait impressions by including psychological codeterminants (e.g., intelligence, perceptual attitude, practice, and attributes of the task and its context). The multivariate nature of Brunswik's research became important for multi-method thinking because its results suggested that measurement methods relying on human perception and judgment can hardly ever be perfectly valid. Second, Brunswik described the many ways in which relative consistencies can be defined in the multivariate space. He discussed several types of correlations and defined validity as convergence among tests. Third, Brunswik claimed that the multivariate approach was not only essential for the description of individuals but also for the classification of other psychological entities like stimuli and situations.

Each situation is a 'variate package,' that is, a more or less incidental combination of specific values along a large, and indeed unknown, number of dimensions. Ecologies, and the situations that constitute them, are in many ways like persons, which also are variate packages. Ecologies or situations exhibit consistencies and 'habits' all of their own, although perhaps less strikingly than do individuals; we may 'know' them and like or dislike them as we do our fellow men. It is by virtue of these relative consistencies that variate packages as a whole, and not their isolated dimensions, should be taken to define a universe. (Brunswik, 1956, p. 139)

The quest for representative design and representative sampling was a fourth important contribution. Brunswik, concerned about the generalizability of experimental results, warned that their ecological validity will be limited if experimental designs and samples are nonrepresentative. Designs are nonrep-resentative when they ignore correlations among dimensions of the data box in the real world. Individuals select situations, types, and modes of behavior are confounded, and situations and time cannot be combined at will. Brunswik illustrated this issue with reference to his own research on the validity of physiognomic trait impressions for personality and ability judgment. In his early studies, Brunswik used schematized drawings and fully crossed facial properties (e.g., eye separation and forehead height) for creating "Gestalten" (holistic impressions). Later, he recognized that such an orthogonal design violates the natural correlation among facial facets and continued his research with photographs of real people. He argued that untying correlated facets of the data box via orthogonal designs violates the principle of representative covariation. This issue is important for multimethod assessment. Methods cannot be crossed at will with properties of psychological objects. Abilities cannot be measured with the same methods as emotions, and implicit attitudes cannot be measured with the same methods as explicit attitudes. Constructs and assessment methods are units that cannot be untied easily. Brunswik was also concerned about the double standards for sampling the person facet versus sampling other facets of the data box. He desired to improve ecological validity in multivariate research via representative sampling on all dimensions. It is difficult to know what this means for the method dimension, because the universe of methods can be less well-defined than the universe of persons. Despite this difficulty, researchers should be sensitive to the issue and careful when generalizing results across methods without considering the range of methods that could be conceived.

Finally, Brunswik's lens model provides a flexible tool for conceptualizing multimethod designs and the effects of multidetermination on convergence (Wittmann, 1988). Figure 2.2 schematically depicts the lens model as a path diagram. The corpus of the lens contains three traits (TA, TB, TC). The foci of the lens represent two methods (Ml, M2). The loadings of the traits are symbolized as arrows. The curved lines in the corpus indicate correlations among the traits. The curved line between the methods represents their correlation. Its size depends on the correlation among the traits and the factor loadings. Perfect convergence of the methods occurs, for instance, if each method measures only one trait and if this trait was the same for both methods. Perfect divergence also occurs if both methods had no trait-factor in common and if the traits were independent.

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