The Effect of Data Characteristics on Theoretical Conclusions Concerning the Physiology of Emotions

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Abstract
Broadly speaking, there are 3 current views pertaining to the physiology of emotions: differential patterns; excitation, and idiosyncratic patterns. All of these have been well supported by research where reliability (statistical significance) is the criterion. Of concern here is whether the choice of data characteristics i.e., the poststimulation state, the change concomitant with stimulation, or either of these statistically adjusted for the prestimulation state determines which theoretical interpretation the investigator is apt to choose. Twenty-four subjects were put through a variety of circumstances, and diverse physiological measurements continually recorded. The data were digitized for all 4 characteristics; then each was subjected to a component of variance analysis with the theoretical views as the treatment effects. Unlike the more common analysis of variance, these analyses yield the percentage of variance accounted for by the differing views under the different data characteristic conditions. It was found that the choice of data characteristic did indeed determine the theoretical interpretation an experimenter would be apt to make. Patterns do not emerge with state scores, excitation emerges weakly in all transforms, activation level manifests itself only in state scores, and idiosyncratic patterns are much in evidence in state scores but also powerful in both of the prestimulation-adjusted scores.

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