Factorial Survey Method (Rossi's Method)

Rossi's factorial survey method, proposed by sociologist Peter Rossi, is a technique that uses vignettes to explore individuals' beliefs and judgments. The method begins with a particular view of human nature. In this view, humans seek to know the causes of things, and they judge (evaluate) the “goodness” or “badness” of things. The drive to understand the way the world works produces positive ideas, and the drive to judge the world produces normative ideas. These positive and normative ideas can be represented by equations, termed, respectively, the positive-belief equation and the normative-judgment equation. In the positive-belief equation, also known as a “what is” equation, the individual-observer is acting as a lay scientist, whereas in the normative-belief equation, also known as a “what ought to be” equation, the individual-observer is acting as a lay judge. Rossi's factorial survey method makes it possible to estimate these equations-inside-the-head.

For example, individuals form ideas about the causes of healthiness and marital happiness, about what generates earnings and produces social harmony, and about many other matters. And they make judgments about fair compensation for workers and chief executive officers, just prison sentences, policies on trade and immigration, and so forth.

Because people differ in their life experience, social location, and information—and also in personality and culture—they may have differing perceptions about the actual world and different ideas about the just world. Thus, the positive-belief and normative-judgment equations are linked to a further equation, which describes the determinants of components of the beliefs or judgments: This equation is called a determinants equation.

For example, the lay scientist's view of the causes of marital happiness may be influenced by childhood observation of parental behavior, and the lay judge's view of the just prison sentence may be influenced by religious experience.

Moreover, beliefs and judgments influence many behaviors. Thus, the positive-belief and normative-judgment equations are linked to another equation, this one describing the consequences of components of the beliefs or judgments. This is called a consequences equation.

For example, the decision to stop smoking or the choice of a marital partner may be influenced by the positive-belief equations about healthiness and marital happiness, respectively. And the decision to participate in a strike or to make a contribution to a lobby group may be influenced by the normative-judgment equations about societal and institutional arrangements.

These four equations—(1) the positive-belief equation, (2) the normative-judgment equation, (3) the determinants equation, and (4) the consequences equation= constitute the basic set of equations in the factorial survey method. They are known, respectively, as Type II, III, IV, and V equations. (Type I is reserved for scientific approximation of the way the world works. Thus, a Type I equation represents a collective and systematic approximation to “truth,” and a Type II equation represents a solitary and less explicitly systematic approximation=a Platonic “appearance” as seen by a given individual.)

The links between the four basic equations may be represented diagrammatically:

Thus, the positive-belief equation and the normative-judgment equation each may join with a determinants equation to form a multi-level system of equations. Similarly, the positive-belief equation and the normative-judgment equation each may join with a consequences equation to form another (possibly multi-level) system of equations.

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