What does incremental validity measure?

What does incremental validity measure?

• A. The correlation between predictor and job performance
• B. The overall reliability of the predictor
• C. The increase in decision-making accuracy resulting from using a predictor
• D. The base rate of hiring decisions

Answer: (C)

Incremental validity is about the added predictive value of a new predictor once you’ve already included other predictors. It answers whether bringing in this predictor improves the accuracy of predicting job performance beyond what your existing model already achieves. In practice, you compare a model with the predictor to a model without it and look for an increase in predictive accuracy, often seen as an increase in explained variance (R-squared). This is exactly what the option describing an increase in decision-making accuracy from using the predictor is capturing. It’s not simply the predictor’s correlation with performance (that’s a basic validity correlation), not about reliability (consistency of the measure), and not about base rates (prior hiring probabilities).

Incremental validity is about the added predictive value of a new predictor once you’ve already included other predictors. It answers whether bringing in this predictor improves the accuracy of predicting job performance beyond what your existing model already achieves. In practice, you compare a model with the predictor to a model without it and look for an increase in predictive accuracy, often seen as an increase in explained variance (R-squared). This is exactly what the option describing an increase in decision-making accuracy from using the predictor is capturing. It’s not simply the predictor’s correlation with performance (that’s a basic validity correlation), not about reliability (consistency of the measure), and not about base rates (prior hiring probabilities).