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Topics in Cognitive Science

A Quantum Question Order Model Supported by Empirical Tests of anA Prioriand Precise Prediction

Zheng Wang, Jerome R. Busemeyer

Published Sep 11, 2013• 220 citations
Publisher

Abstract

Question order effects are commonly observed in self-report measures of judgment and attitude. This article develops a quantum question order model (the QQ model) to account for four types of question order effects observed in literature. First, the postulates of the QQ model are presented. Second, an a priori, parameter-free, and precise prediction, called the QQ equality, is derived from these mathematical principles, and six empirical data sets are used to test the prediction. Third, a new index is derived from the model to measure similarity between questions. Fourth, we show that in contrast to the QQ model, Bayesian and Markov models do not generally satisfy the QQ equality and thus cannot account for the reported empirical data that support this equality. Finally, we describe the conditions under which order effects are predicted to occur, and we review a broader range of findings that are encompassed by these very same quantum principles. We conclude that quantum probability theory, initially invented to explain order effects on measurements in physics, appears to be a powerful natural explanation for order effects of self-report measures in social and behavioral sciences, too.

DOI
10.1111/tops.12040

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Question order effects are commonly observed in self-report measures of judgment and attitude. This article develops a quantum question order model (the QQ model) to account for four types of question order effects observed in literature. First, the postulates of the QQ model are presented. Second, an a priori, parameter-free, and precise prediction, called the QQ equality, is derived from these mathematical principles, and six empirical data sets are used to test the prediction. Third, a new index is derived from the model to measure similarity between questions. Fourth, we show that in contrast to the QQ model, Bayesian and Markov models do not generally satisfy the QQ equality and thus cannot account for the reported empirical data that support this equality. Finally, we describe the conditions under which order effects are predicted to occur, and we review a broader range of findings that are encompassed by these very same quantum principles. We conclude that quantum probability theory, initially invented to explain order effects on measurements in physics, appears to be a powerful natural explanation for order effects of self-report measures in social and behavioral sciences, too.
The hypothesis that human reasoning obeys the laws of quantum rather than classical probability has been used in recent years to explain a variety of seemingly "irrational" judgment and decision-making findings. This article provides independent evidence for this hypothesis based on an a priori prediction, called the quantum question (QQ) equality, concerning the effect of asking attitude questions successively in different orders. We empirically evaluated the predicted QQ equality using 70 national representative surveys and two laboratory experiments that manipulated question orders. Each national study contained 651-3,006 participants. The results provided strong support for the predicted QQ equality. These findings suggest that quantum probability theory, initially invented to explain noncommutativity of measurements in physics, provides a simple account for a surprising regularity regarding measurement order effects in social and behavioral science.
Recent findings show that human inferences and decisions interfere in ways analogous to incompatible quantum observables, and conceptual judgments are inseparable in ways similar to entangled quantum states.This discovery has led a group of physicists and psychologists to form a new field called "quantum cognition," which uses mathematical principles of quantum theory to explain human cognitive behavior.The power of this new theoretical approach is illustrated here by testing an a priori and precise prediction derived from quantum theory regarding question order effects commonly observed in survey research.The test of quantum theory was statistically satisfied across a set of 26 national surveys on presidential job approval and country satisfaction in past 10 years.These results suggest that quantum theory, initially invented to explain order effects on measurements in physics, provides a powerful prediction for measurement order effects in social and behavioral sciences too.
The order effect is a well-known phenomenon in cognitive psychology which violates specific axioms of the classical probability theory and refers to different probabilities of measurement outcomes (answers to questions) depending on their order. In this research, the order effect was analyzed using quantum probabilistic modeling of cognitive processes. The Quantum Question (QQ) model suggested by Wang and Busemeyer (2013) was tested on a sample of participants that had answered three yes/no questions about a painting, in different orders. For that purpose, three problems were considered. The first problem was to examine the presence of the order effect in participants’ answers and the results showed order effects for all three questions. The second problem was to test data fitness with a model prediction called QQ equality and the data proved to be a good fit to the model. The purpose of the third problem was to examine the dependency of the q value derived from the model on a third question. Given that the QQ equality is a prediction which includes only two yes/no questions, an additional prediction was derived from the model which includes a third question and according to which, the q value is independent of a third question. The results showed a limitation in the model in explaining empirical data. A proposal was made how to expand the theory, so it would include models with three or more questions.
Can one really predict something new and interesting using quantum theory in the social or behavioral sciences? Consider the law of reciprocity described in Chapter 2: according to this law, the probability of transiting from one state to another is equal to the probability of making this transition in the opposite direction. Now this symmetrical property is a pretty bold prediction to make in the social and behavioral sciences. Does this really work? To answer this question, in this chapter we empirically test this law by applying the quantum principles to an important empirical problem concerning the effects of question order on attitude judgments. For example, suppose you are asked “How happy are you with life in general?” This question could be preceded or followed by the question “How happy are you with your marriage?” If the marriage question comes first, then the happiness rating for the general life question tends to be substantially depressed, producing a large order effect (Tourangeau et al ., 1991). Quantum physics was originally developed to understand how measurement affects the system under investigation, which led to Heisenberg's famous uncertainty principle. The potential reactivity to measurement by the person being measured has an even longer history in psychology (Tourangeau et al ., 2000). The effects of question order have been an important issue to survey researchers interested in studying beliefs and attitudes (Schuman & Presser, 1981). Measurement of a belief or attitude directs attention to a subset of a person's knowledge, which is then used in guiding subsequent judgments.
Lately, so-called 'quantum models' based on parts of the mathematics of quantum mechanics, have been developed in decision theory and cognitive sciences to account for seemingly irrational or paradoxical human judgments. In this paper, we limit ourselves to such quantum-like models that address order effects. It has been argued that such models are able to account for existing and new empirical data, and meet some a priori predictions. From the quantum law of reciprocity, we derive new empirical predictions that we call the Grand Reciprocity equations, that must be satisfied by quantum-like models on the condition that they are non-degenerate. We show that existing non-degenerate quantum-like models for order effects fail this test on several existing data sets. We take it to suggest that degenerate quantum-like models should be the focus of forthcoming research in the area.
We continue to analyze basic constraints on human's decision making from the viewpoint of quantum measurement theory (QMT). As has been found, the conventional QMT based on the projection postulate cannot account for combination of the question order effect (QOE) and the response replicability effect (RRE). This was an alarm signal for quantum-like modeling of decision making. Recently, it was shown that this objection to quantum-like modeling can be removed on the basis of the general QMT based on quantum instruments. In the present paper we analyse the problem of combination of QOE, RRE, and the famous QQ-equality (QQE). This equality was derived by Busemeyer and Wang and it was shown (in the joint paper with Solloway and Shiffrin) that statistical data from many social opinion polls satisfies it. Now, we construct quantum instruments satisfying QOE, RRE, and QQE. The general features of our approach are formalized with postulates which generalize {\it Wang-Busemeyer} postulates for quantum-like modeling of decision making. Moreover, we show that our model closely reproduces the statistics of the famous Clinton-Gore Poll data with a prior belief state independent of the question order. This model successfully removes the order effect from the data to determine the genuine distribution of the opinions in the Poll. The paper also provides a psychologist-friendly introduction to the theory of quantum instruments - the most general mathematical framework for quantum measurements. We hope that this theory will attract attention of psychologists and will stimulate further applications.