Often, personnel selection practitioners present the results of their criterion-related validity studies to their senior leaders and other stakeholders when trying to either implement a new test or validate an existing test. It is sometimes challenging to present complex, statistical results to non-statistical audiences in a way that enables intuitive decision making. Therefore, practitioners often turn to expectancy charts to depict criterion-related validity. There are two main approaches for constructing expectancy charts (i.e., use of Taylor-Russell tables or splitting a raw dataset), both of which have considerable limitations. We propose a new approach for creating expectancy charts based on the bivariate-normal distribution. The new method overcomes the limitations inherent in the other two methods and offers a statistically sound and user-friendly approach for constructing expectancy charts.

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Jeffrey M. Cucina



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