Kelley's Covariation Model

Definition

Harold Kelley's covariation principle is a central model within attribution theory, an area of social psychology that is concerned with the scientific analysis of the psychology of everyday people. Attribution theory was originally introduced by Fritz Heider in 1958 and assumes that we all want to understand and explain events. For instance, we ask why we succeeded at a task or why our friend liked a movie. The answers to such “why questions” (e.g., “I am smart” or “The movie was good”) are called causal attributions. Kelley's model explains how laypersons arrive at such attributions; hence, it is a scientific theory about naive theories.

Analysis

For both scientists and laypersons, explanations consist of effects to be explained (e.g., success at a task or liking a movie) and causes that are used as explanations (e.g., high ability or the quality of the movie). Kelley's model applies to all types of psychological effects that laypersons explain, ranging from achievement outcomes to emotional states, and it can be applied to self-perception (e.g., “Why did I fail?”) as well as to other perception (“Why did you fail?”).

Kelley distinguishes attributions to causes that reside within the person, the entity, and the circumstances. Person attributions (e.g., “She is a movie fanatic” or “She is smart”) rely on stable factors residing within the person to explain, for example, that person's enjoyment of a movie or his or her success. Entity attributions imply tracing back the effect to stable properties of the object the person interacts with (e.g., we explain the enjoyment with the quality of the movie, or success with task ease). Finally, circumstance attributions are made when explaining an effect with transient and unstable causes (e.g., when enjoyment is traced back to a happy mood or success is attributed to luck).

But how do we come to explain a specific effect with one of such causes?

Kelley postulates that laypersons use methods akin to those used by scientists, most importantly, experiments. In such experiments, independent and dependent variables are differentiated. For instance, a researcher investigating the influence of color on mood will manipulate color as the independent variable (e.g., putting half of the participants in a blue room and the other half in a red room). Subsequently, she assesses, as the dependent variable, participants' mood in both rooms. In such experiments, the independent variables are often conceived of as causes or determinants of the dependent variables (e.g., color might be conceived of as a determinant of mood), and the dependent variables are the effects.

From this point of view, events to be explained by lay scientists (e.g., success or liking a movie) are the dependent variable, and the possible causes of the event are independent variables. For instance, when I succeed at a task and I ask myself, “Why did I succeed?” success is the dependent variable (i.e., the effect) and the possible causes—the task (entity), my ability (person), or luck (circumstances)—are independent variables.

[Page 518]Whether an effect is attributed to the person, the entity, or the circumstances depends on which of the causes (independent variables) the effect (dependent variable) covaries with. Covariation refers to the cooccurrence of the effect and a cause. To decide whether the entity is the cause, one has to assess whether the effect covaries (co-occurs) with the entity—more specifically, whether there is variation of the effect across objects (entities). Covariation with the entity is given when the effect is present if the entity is present and when the effect is absent when the entity is absent. For instance, when a person succeeds at Task 1 but fails at Tasks 2, 3 and 4, the effect (i.e., success) is present when Task 1 (i.e., the entity) is present, and it is absent when Task 1 is absent (i.e., when Tasks 2, 3, and 4 are present). In this example, the effect covaries with the task (entity): The manipulation of this independent variable results in an effect of the dependent variable; that is, the task “makes a difference.” If, however, the individual succeeds at all tasks in addition to Task 1, the effect (success) does not vary with tasks (there is no covariation between the effect and the entity), or the manipulation of the independent variable (task) does not result in a change of the dependent variable (outcome).

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