Covariation and causal attribution: A Logical Model of the intuitive analysis of variance.

Abstract

In this article, we present and test a formal model of carnal attribution that is true to the original conception of attribution theory formulated by Kelley (1967). The Logical Model specifies precisely how information might be encoded from attribution^ vignettes and how subjects might consider different causal loci as necessary and sufficient conditions for the occurrence of an effect. Predictions are derived for each of the eight information configurations on the basis of consensus, distinctiveness, and consistency information. The model is tested with data from three published experiments and is preferred over a template model of attribution. The Logical Model's limitations are also acknowledged in that responses deviate systematically from its predictions, leading to an analysis of the notion of causality underlying stimulus, person, and circumstance attributions.The logic of science is also that of business and life.-John Stuart Mill 'Contrariwise,' continued Tweedledee, 'if it was so, it might be; and if it were so, it would be: but as it isn't, it ain't. That's logic.' -Lewis Carroll, Through The Looking Glass Kelley's (1967) theory of causal attribution proposes that in the case where the perceiver has information from multiple sources, the covariation principle is used. An effect is attributed to the cause with which it covaries over time.In outlining attribution in the case of covariation, Kelley built onto Heider's (1958) proposal that understanding of the distal environment is gained by means of a causal analysis that is "in a way analogous to experimental methods" (p. 297). Kelley was influenced both by Heider's suggestion that social perception was similar to a naive "factor analysis" (Heider, 1958, p. 66) and by Duncker's proposal that cause and effect analysis was achieved by a pseudoscientific "abstracting induction" (Dunckei, 1945, p. 64). In addition, Kelley followed Heider in the use of a naive version of 3. S. Mill's method of difference: "The effect is attributed to that condition which is present when the effect is present and which is absent when the effect is absent" (Kelley, 1967,p. 194). Thus the notion of covariation was conceived, the underlying logic of which, Kelley argued, was similar to that of the analysis of variance (ANOVA).The essence of the ANOVA model can be demonstrated most clearly by considering an example sentence from McArthur's (1972) study: "John laughs at the comedian." This outcome Much of this article was conceptualized before the tragic death of Jos Jaspars. Although it is published as a tribute to bis scholarly work in the area of attribution, it should not be taken as a definitive statement of his views; Miles Hewstone must take full responsibility for its exact content.We gratefully acknowledge critical comments by Denis Hilton, Charles Judd, and two anonymous reviewers on an earlier version of this article.

Covariation in natural causal induction.

“…It is not obvious how these models can be generalized to account for conjunctive probabilistic causes, even if the probabilistic generalization for simple causes is straightforward. In social psychology, in which the phenomena to be explained are clearly probabilistic, some of the models are nonetheless deterministic (e.g., Forsterling, 1989;Hewstone & Jaspars, 1987;Jaspars, 1983; the covariation principle in Kelley, 1967Kelley, , 1973. Of those that are not, none provides a formal definition of conjunctive causes (e.g., Hilton & Slugoski, 1986; the ANOVA analogy in Kelley, 1967Kelley, ,1973McGill, 1989;see Cheng & Novick, 1990a, for a discussion of these models).…”

“…The causal attribution literature in social psychology has largely measured performance against an apparently different normative standard: namely, variations of Kelley's (1967Kelley's ( ,1973 influential proposal that people are "intuitive scientists" who use a mechanism of causal induction analogous to the analysis of variance (ANOVA) (Cheng & Novick, 1990a;Forsterling, 1989;Hewstone & Jaspars, 1987;Hilton, 1988Hilton, ,1990Jaspars, 1983;Orvis, Cunningham, & Kelley, 1975;Pruitt & Insko, 1980). This literature has, until recently, presented a chaotic picture of causal induction not unlike that in cognitive psychology: Causal induction sometimes conforms to the normative standard but often deviates from it.…”

Covariation and quantifier polarity: What determines causal attribution in vignettes?

“…events in the real world, and from these instances they compute co-occurrence between the events to make causal attributions (Cheng & Novick, 1990;Försterling, Buhner, & Gall, 1998;Hewstone & Jaspers, 1987;Hilton & Slugoski, 1986;Orvis, Cunningham, & Kelley, 1975;Pruitt & Insko, 1980;Sutton & McClure, 2001).…”

“…almost any, everyone, many, hardly anyone, few, and nobody (e.g. Cheng & Novick, 1990;Hewstone & Jaspers, 1987;Hilton & Jaspars, 1987;Hilton, Smith, & Kim, 1995;McArthur, 1972McArthur, , 1976Pruitt & Insko, 1980;Rudolph, 1997;Smith & Miller, 1979;Sutton & McClure, 2001;Van Overwalle, 1998;Van Overwalle & Heylighen, 1995). The assumption is that the difference between quantifiers is in the set sizes they denote, and so any difference in causal attribution must be due to set size.…”

Contemporary Knowledge Engineering and Cognition

“…The knowledge structures used when making attributions is seen as the content (see also Galambos et al, 1986). Kelley's (1983) covariation model has been contrasted with Hewstone's and Jaspars (1987) logical model for identifying necessary and sufficient conditions for causal attribution. The logical model helps delineate all possible combination of causes for consideration.…”