Standardized covariance—A measure of association, similarity and co-riskiness between choice options

• We propose a measure of association, similarity and co-riskiness of choice options.
• The measure is similar to correlation, but can be applied to two-outcome options.
• It differs from correlation by providing a non-linear measure of association.
• It measures the risk of one option with respect to the other.
• It can influence predictions of choice models and human preferences.

Predictions of prominent theories of decision making, such as decision field theory and regret theory, strongly depend on the association between outcomes of choice options. In the present work, we show that these associations reflect the similarity of two choice options and riskiness of one option with respect to the other. We propose a measure labeled standardized covariance that can capture the strength of the association, similarity and co-riskiness between two choice options. We describe the properties and interpretation of this measure and show its similarities to and differences from the correlation measure. Finally, we show how the predictions of different models of decision making vary depending on the value of the standardized covariance, which can have implications for research on decision making under risk.