The impact of corrections for faking on the validity of noncognitive measures in selection settings

In selection research and practice, there have been many attempts to correct scores on noncognitive measures for applicants who may have faked their responses somehow. A related approach with more impact would be identifying and removing faking applicants from consideration for employment entirely, replacing them with high-scoring alternatives. The current study demonstrates that under typical conditions found in selection, even this latter approach has minimal impact on mean performance levels. Results indicate about .1 SD change in mean performance across a range of typical correlations between a faking measure and the criterion. Where trait scores were corrected only for suspected faking, and applicants not removed or replaced, the minimal impact the authors found on mean performance was reduced even further. By comparison, the impact of selection ratio and test validity is much larger across a range of realistic levels of selection ratios and validities. If selection researchers are interested only in maximizing predicted performance or validity, the use of faking measures to correct scores or remove applicants from further employment consideration will produce minimal effects.